Chemie und Prozesstechnik
Filtern
Dokumenttyp
- Zeitschriftenartikel (1183)
- Vortrag (1072)
- Posterpräsentation (443)
- Beitrag zu einem Tagungsband (175)
- Forschungsdatensatz (56)
- Sonstiges (30)
- Buchkapitel (24)
- Forschungsbericht (23)
- Dissertation (15)
- Beitrag zu einem Sammelband (13)
Sprache
- Englisch (3065) (entfernen)
Schlagworte
- Nanoparticles (114)
- Fluorescence (111)
- Concrete (89)
- LIBS (81)
- Mechanochemistry (72)
- Quantum yield (72)
- Ultrasound (71)
- SAXS (69)
- Non-destructive testing (68)
- Nanoparticle (63)
Organisationseinheit der BAM
- 1 Analytische Chemie; Referenzmaterialien (1092)
- 6 Materialchemie (980)
- 8 Zerstörungsfreie Prüfung (775)
- 6.1 Oberflächen- und Dünnschichtanalyse (348)
- 6.3 Strukturanalytik (328)
- 1.1 Anorganische Spurenanalytik (277)
- 8.2 Zerstörungsfreie Prüfmethoden für das Bauwesen (232)
- 1.2 Biophotonik (214)
- 4 Material und Umwelt (186)
- 8.5 Röntgenbildgebung (169)
Paper des Monats
- ja (27)
Laser powder bed fusion is one of the most promising additive manufacturing techniques for printing complex-shaped metal components. However, the formation of subsurface porosity poses a significant risk to the service lifetime of the printed parts. In-situ monitoring offers the possibility to detect porosity already during manufacturing. Thereby, process feedback control or a manual process interruption to cut financial losses is enabled.
Short-wave infrared thermography can monitor the thermal history of manufactured parts which is closely connected to the probability of porosity formation. Artificial intelligence methods are increasingly used for porosity prediction from the obtained large amounts of complex monitoring data. In this study, we aim to identify the potential and the challenges of deep-learning-assisted porosity prediction based on thermographic in-situ monitoring.
Therefore, the porosity prediction task is studied in detail using an exemplary dataset from the manufacturing of two Haynes282 cuboid components. Our trained 1D convolutional neural network model shows high performance (R2 score of 0.90) for the prediction of local porosity in discrete sub-volumes with dimensions of (700 x 700 x 40) μm³.
It could be demonstrated that the regressor correctly predicts layer-wise porosity changes but presumably has limited capability to predict differences in local porosity. Furthermore, there is a need to study the significance of the used thermogram feature inputs to streamline the model and to adjust the monitoring hardware. Moreover, we identified multiple sources of data uncertainty resulting from the in-situ monitoring setup, the registration with the ground truth X-ray-computed tomography data and the used pre-processing workflow that might influence the model’s performance detrimentally.
The contamination of drinking water with pharmaceuticals represents a severe health risk. In order to monitor the drinking water quality continuously and enable quick countermeasures in case of contamination, novel sensors are required. Here, immunoanalytical methods based on the binding of the analyte to highly selective antibodies can be helpful. In this work, magnetic bead-based immunoassays (MBBAs) have been developed for the detection of two relevant contaminants of drinking water: diclofenac (DCF) and amoxicillin (AMX). In case of the latter, not only the parent drug is of interest in the risk assessment but also its hydrolysis products (HPs). In a comprehensive study, the influence of external factors and intrinsic properties of the water on the rate of hydrolysis was investigated. As the hydrolysis of AMX further impacts the recognition by the antibody, a strategy to analyze samples with unknown hydrolysis degree of AMX was established employing the enzyme β-lactamase in sample preparation. For both analytes, the MBBAs enable the fast quantification with results obtained in less than one hour which represents a major improvement over conventional immunoassays like the enzyme-linked immunosorbent assay (ELISA). Compared to the respective ELISAs with the same antibodies, the MBBAs further exhibit improved analytical parameters such as a broader measurement range and lower limits of detection. Due to the magnetic properties of the beads that serve as a platform for the assays, they are suitable for the mobile and automated detection at the point-of-care. An integrated diagnostic system was designed in which electrochemical detection with chronoamperometry on a microfluidic chip allows for further miniaturization of the system to enable monitoring of the drinking water quality online in water supply pipes at waterworks.
The statistical tool eCerto was developed for the evaluation of measurement data to assign property values and associated uncertainties of reference materials. The analysis is based on collaborative studies of expert laboratories and was implemented using the R software environment. Emphasis was put on comparability of eCerto with SoftCRM, a statistical tool based on the certification strategy of the former Community Bureau of Reference. Additionally, special attention was directed towards easy usability from data collection through processing, archiving, and reporting. While the effects of outlier removal can be flexibly explored, eCerto always retains the original data set and any manipulation such as outlier removal is (graphically and tabularly) documented adequately in the report. As a major reference materials producer, the Bundesanstalt für Materialforschung und -prüfung (BAM) developed and will maintain a tool to meet the needs of modern data processing, documentation requirements, and emerging fields of RM activity. The main features of eCerto are discussed using previously certified reference materials.
The European Commission has identified Advanced Manufacturing and Advanced Materials as two of six Key Enabling Technologies (KETs). It is considered that Metrology is a key enabler for the advancement of these KETs. Consequently, EURAMET, the association of metrology institutes in Europe, has strengthened the role of Metrology for these KETs by enabling the creation of a European Metrology Network (EMN) for Advanced Manufacturing. The EMN is comprised of National Metrology Institutes (NMIs) and Designated Institutes (DIs) from across Europe and was formally established in October 2021. The aim of the EMN is to provide a high-level coordination of European metrology activities for the Advanced Manufacturing community.
The EMN itself is organized in three sections representing the major stages of the manufacturing chain: 1) Advanced Materials, 2) Smart Manufacturing Systems, and 3) Manufactured Components & Products. The EMN for Advanced Manufacturing is engaging with stakeholders in the field of Advanced Manufacturing (large companies & SMEs, industry organisations, existing networks, and academia), as well as the wider Metrology community, including Technical Committees, to provide input for the Strategic Research Agenda (SRA) on Metrology for Advanced Manufacturing.
This contribution will give an overview about the first version of the SRA prepared by the EMN for Advanced Manufacturing.
Human factors (HFs) are a frequently mentioned topic when talking about the reliability of non-destructive testing (NDT). However, probability of detection (POD), the commonly used measure of NDT reliability, only looks at the technical capability of an NDT system to detect a defect.
After several decades of research on the influence of HFs on NDT reliability, there is still no commonly accepted approach to rendering HFs visible in reliability assessment. This paper provides an overview of possible quantitative and qualitative methods for integrating HFs into the reliability assessment. It is concluded that reliability assessment is best carried out using both quantifiable and non-quantifiable approaches to HFs.
Concrete is the most important human-made material because it serves as the basis of our built environment. Since the properties of concretes are dominated by their key compound, cement, devising a way to determine the cement’s origin, known as provenancing, is of great importance for answering different provenance-related questions. These questions range from liability issues when damage occurs to concrete-made structures, to forensic investigations where cement particles are found at crime scenes. This thesis showcases the use of isotope techniques to answer these provenance-related questions. Conventional 87Sr/86Sr and 143Nd/144Nd isotope and elemental ratios consisting of Ca, Sr, K, Mn, Mg, and Ti are used as fingerprints for ordinary Portland cement (OPC) provenancing. The first part of this thesis describes research previously conducted in fingerprinting cementitious materials, providing an overview of provenance studies of cement and the main approaches commonly used. In several studies, the origin of clinker for certain locations was determined via different approaches. However, clinker is an intermediate product, which is available only at the production site and therefore, the practical relevance is rather limited. Furthermore, the use of Sr and Nd isotope systems, together with elemental fingerprints are presented as state of the art in the field. Therein, the principal approach for the overall study is sketched. For the second part of the study, a sample preparation technique for Sr isotopes in Portland cement was developed. The aim was to find the most appropriate sample preparation procedure for cement provenancing and selection was realised by comparing the 87Sr/86Sr isotope ratios of differently treated OPCs with those of the corresponding clinkers. Based on these findings, the third part of the study focused on the measurements of Sr and Nd isotope ratios, together with elemental ratios, to establish a reliable technique for OPC provenancing. The outcomes of this final stage are then used to establish a procedure for fingerprinting cements. This becomes possible with the use of Sr and Nd isotope ratios and geochemical profiles. To perform isotope ratio measurements and obtain reliable data, it was necessary to establish a quality control procedure. Thus, an interlaboratory comparison (ILC) was organised to characterise 87Sr/86Sr isotope ratios in geological and industrial reference materials by applying the conventional method for 87Sr/86Sr isotope ratios. As reference material, four cements (VDZ 100a, VDZ 200a, VDZ 300a, IAG OPC-1), one limestone (IAG/CGL ML-3) and one slate (IAG OU-6) were selected, thus covering a wide range of Sr isotope signatures.
Sr isotope ratio analysis
(2023)
Pb isotope ratio analysis
(2023)
Detector deadtime
(2023)
Isotope Ratio Analysis
(2023)
The through-life management of our constantly ageing infrastructure is a basic requirement in order to ensure their structural safety and serviceability. Each structure experiences deterioration processes with time leading to a decrease of structural safety and serviceability. The design of new structures considers the expected deterioration for a defined period, the design service life. However, a frequent survey of structural safety controlling structural condition should be mandatory and a maintenance plan should be an integral part of the design. In addition, many structures have exceeded their design service life already or are very close to it leading to an increasing demand for condition assessment. On the one hand, assumptions made during design are not valid any more due to change of the loads, e.g., increasing traffic loads in terms of number and weights. On the other hand, design codes evolved over time in such a way that existing structures do not comply with today’s standards. In all these cases, the through-life management is an important tool to maintain the accessibility of existing structures with known reliability.
In line with the new Model Code for Concrete Structures, which includes guidance for both – design of new structures and assessment of existing structures, the Task Group 3.3 focused on the compilation of a state-of-the-art guideline for the through-life management of existing concrete structures, including:
Data acquisition by testing and monitoring techniques;
Condition assessment for the evaluation of existing structures;
Performance prediction using advanced methods;
Decision-making procedures to perform a complete assessment of existing structure.
The overall objective of the through-life management is the assessment of the current condition and the estimation of the remaining service life under consideration of all boundary conditions.
Here, we elucidate nonclassical multistep crystallization pathways of transition metal phosphates from aqueous solutions. We followed precipitation processes of M-struvites, NH4MPO4·6H2O, and M-phosphate octahydrates, M3(PO4)2·8H2O, where M = Ni, Co, or NixCo1–x, by using in situ scattering and spectroscopy-based techniques, supported by elemental mass spectrometry analyses and advanced electron microscopy. Ni and Co phosphates crystallize via intermediate colloidal amorphous nanophases, which change their complex structures while agglomerating, condensing, and densifying throughout the extended reaction times. We reconstructed the three-dimensional morphology of these precursors by employing cryo-electron tomography (cryo-ET). We found that the complex interplay between metastable amorphous colloids and protocrystalline units determines the reaction pathways. Ultimately, the same crystalline structure, such as struvite, is formed. However, the multistep process stages vary in complexity and can last from a few minutes to several hours depending on the selected transition metal(s), their concentration, and the Ni/Co ratio.
Surface functionalized silica nanoparticles (SiO2-NP) gained great interest in the life and material sciences, as they can be used e.g. as drug carriers, fluorescent sensors, and multimodal labels in bioanalytical assays and imaging applications. They are highly stable, are easily produced and modified on a large scale at low cost and can be labeled or stained with a multitude of sensor dyes. These dye modified particle conjugates have several advantages as compared to conventional molecular probes like enhanced brightness, ease of designing ratiometric systems by combining analyte-sensitive and inert reference dyes, and increased photostability. Moreover, stained nanoparticles can enable the use of hydrophobic dyes in aqueous environments.
Here we present our work on multicolored sensors for the measurement of pH, oxygen and saccharides utilizing amorphous SiO2 NPs.
In recent years, chromium (III) complexes have received a lot of attention as novel near-infrared (NIR) emitters triggered by the report on the first molecular ruby Cr(ddpd)2(BF4)3 with a high photoluminescence quantum yield of 13.7% of its near infrared (NIR) emission band and a long luminescence lifetime of 1.122 ms at room temperature.[1] However, in an oxygen-containing environment, the photoluminescence quantum yields and luminescence lifetimes of these chromium(III) complexes show only very small values. This hampers their application as NIR luminescence labels. This application, that cannot be tackled by conventional deoxygenating approaches, requires suitable strategies to protect the luminescence of the chromium(III) complexes from oxygen quenching. An elegant approach to reduce the undesired luminescence quenching by triplet oxygen explored by us presents the incorporation of these chromium(III) complexes into different types of amorphous, non-porous silica nanoparticles, that can be simply surface functionalized, e.g., with targeting ligands and/or other sensor molecules. In this work, as first proof-of-concept experiments, a set of chromium (III) complexes constituting of different ligands and counter anions, were embedded into the core of silica nanoparticles. Subsequently, the optical properties of the resulting luminescent silica nanoparticles were spectroscopically assessed by steady state and time-resolved luminescence spectroscopy. First results of time-resolved luminescence measurements confirm our design concept of nanoscale NIR emissive Cr(III) complex-based reporters
Engineered nanoparticles (NPs) with various chemical compositions and surface functionalities are routinely fabricated for industrial applications such as medical diagnostics, drug delivery, sensing, catalysis, energy conversion and storage, opto-electronics, and information storage which improve the quality of life and European prosperity. NP function, performance, interaction with biological species, and environmental fate are largely determined by their surface functionalities. Standardized repeatable surface characterization methods are therefore vital for quality control of NPs, and to meet increasing concerns regarding their safety. Therefore, industry, regulatory agencies, and policymakers need validated traceable measurement methods and reference materials. This calls for fit-for-purpose, validated, and standardized methods, and reference data and materials on the surface chemistry of engineered NPs. Here, we present a concept for the development of such standardized measurement protocols utilizing method cross-validation and interlaboratory comparisons (ILCs) with emphasis on both advanced measurement methods such as quantitative Nuclear Magnetic Resonance (qNMR), X-ray photoelectron spectroscopy (XPS) and secondary ion mass spectrometry (SIMS) and cost-efficient, non-surface specific methods like optical assays and electrochemical titration methods.
Engineered and tailored nanomaterials (NM) are of great interest in the life and material sciences, as they can be used, e.g., as drug carriers, barcodes, fluorescent sensors, and multimodal labels in bioanalytical assays and imaging applications. Their performance and safety depend not only on their particle size, size distribution, and morphology, but also on their surface chemistry, i.e., the total number of surface functional groups (FG) and the number of FG accessible for subsequent functionalization with ligands or biomolecules, which in turn determines surface charge, colloidal stability, biocompatibility, and toxicity. It also underlines the importance of validated analytical methods that provide accurate information on these application-relevant physicochemical properties with a known uncertainty. In the case of FG quantification, this calls for robust, fast, inexpensive, and reliable methods which allow for the characterization of a broad variety of NM differing in size, chemical composition, and optical properties.
Methods
Aiming at the development of simple, versatile, and multimodal tools for the quantification of bioanalytically relevant FG such as amine, carboxy, thiol, and aldehyde functionalities, we investigated and compared various analytical methods commonly used for FG quantification. This includes electrochemical titration methods, dye-based optical assays, and other instrumental analytical techniques such as nuclear magnetic resonance (NMR), mass spectrometry (MS), and thermal analysis methods.
Results
Here, we will present examples for different types of NMs and FGs including results from a currently running interlaboratory comparison (ILC) with the National Research Council of Canada (NRC) to pave the road for method standardization.
Innovative aspects
• Surface analysis
• Performance and safety of nanomaterials
• Standardization
Engineered nanomaterials (NM) with their large surface-to-volume ratios and their for some materials observed size-dependent functional properties are of increasing relevance for current and future developments in various fields such as medical and pharmaceutical industry, computing and electronics or food and consumer products. The performance and safety of NM are determined by the sum of their intrinsic physicochemical properties. Especially, the particle surface chemistry, which is largely controlled by the chemical nature and density of functional groups (FG) and ligands, is an important key driver for NM performance, stability, and processibility as well as the interaction of NM with the environment. Thus, methods for FG quantification can foster the sustainable development of functional and safe(r) NM.
Aiming at the development of simple, versatile, and multimodal tools for the quantification of many bioanalytically relevant FG and ligands, we investigated and compared various analytical methods commonly used for FG quantification. This includes electrochemical titration methods, dye-based optical assays, and other instrumental analytical techniques such as nuclear magnetic resonance and thermal analysis methods.
The potential of our multimodal approach for FG quantification was demonstrated for commercial and custom-made polymeric and silica particles of varying FG, used as optical pH sensors. In the future, our strategy can contribute to establish multi-method characterization strategies to provide a more detailed picture of the structure-properties relationship.
In recent years, the use of functionalized micro- and nanomaterials has increased rapidly for a wide range of applications in the life and material sciences, due to their unique properties in combination with their high surface-to-volume ratio and stability. For instance, functionalized micro- and nanomaterials, that are labeled or stained with a multitude of sensor dyes can be used for monitoring, and quantification of neutral and ionic analytes. These materials have several advantages as compared to conventional molecular probes like enhanced brightness, ease of designing ratiometric systems by combining analyte-sensitive and inert reference dyes, and increased photostability. Moreover, stained nanoparticles can enable the use of hydrophobic dyes in aqueous environments.
Versatile templates and carriers for the fabrication of nanosensors by staining and/or labeling with different fluorophores and sensor molecules are biocompatible silica and polymeric particles, because they can be synthesized in large scales at low costs with different surface chemistries.
Here we present our work on multicolored sensors for the measurement of pH, oxygen and saccharides utilizing commercially available or in-house synthesized silica and polymeric particles.
Nowadays amorphous silica nanoparticles (SiO2-NP) are one of the most abundant engineered nanomaterials, that are highly stable and can be easily produced on a large scale at low cost. Surface functionalized SiO2-NP are of great interest in the life and material sciences, as they can be used e.g. as
drug carriers, fluorescent sensors, and multimodal labels in bioanalytical assays and imaging applications. Their performance in such applications depends not only on particle size, size distribution, and morphology, but also on surface chemistry, i.e. the total number of surface functional groups (FG)
and the number of FG accessible for subsequent functionalization with ligands or biomolecules, which in turn determines surface charge, colloidal stability, biocompatibility, and toxicity. Aiming at the development of simple, versatile, and multimodal tools for the quantification of many bioanalytically relevant FG and ligands, we investigated and compared various analytical methods commonly used for FG quantification. This includes electrochemical titration methods, dye-based optical assays, and other instrumental analytical techniques such as nuclear magnetic resonance and thermal analysis methods.
The potential of our multimodal approach for FG quantification was demonstrated for commercial and custom-made silica particles of varying FG, showing not only an influence of the synthesis methods on the number of FG but also on the performance. In the future, our strategy can contribute to establish multi-method characterization strategies to provide a more detailed picture of the structure-properties relationship.
In the focus of division Biophotonics are the design, preparation, analytical and spectroscopic characterization, and application of molecular and nanoscale
functional materials, particularly materials with a photoluminescence in the visible, near infrared (NIR) and short-wave infrared (SWIR). This includes optical reporters for bioimaging and sensing, security and authentication barcodes, and materials for solid state lighting, energy conversion, and photovoltaics. For the identification of optimum particle structures quantitative spectroscopic studies are performed under application-relevant conditions, focusing on the key performance parameter photoluminescence quantum yield. In addition, simple, cost-efficient, and standardizable strategies for quantifying functional groups on the surface of nano- and microparticles are developed, here with a focus on optical assays and electrochemical titration methods, cross-validated by more advanced methods such as quantitative NMR. In addition, reference materials and reference products are developed for optical methods, particularly luminescence techniques, and for analytical methods utilized for the characterization of nanomaterials.
For fluorescence microscopy, there is an increasing need for suitable calibration tools and reference materials for microscope calibration, the determination of performance parameters, and the regular control and validation of instrument performance. This is addressed in the BmWk-financed project FluMikal (WIPANO program) by two research groups from academia and two companies, that is coordinated by BAM. Here we present different approaches to liquid and solid fluorescence standards for the determination of the wavelength-dependent spectral sensitivity of fluorescence microscopes and ideas concerning the choice of suitable fluorescence lifetime standard for increasingly utilized fluorescence lifetime imaging (FLIM).
The digitalization of quality control processes and the underlying data infrastructures for safety relevant components, such as hydrogen pressure vessels, plays a significant role in the transition towards Industry 4.0. In the current safety regulations for hydrogen pressure vessels, there is no established concept for structural health monitoring. The development of a reliable structural health monitoring methodology for monitoring the structural integrity of pressure vessels enables a fast-forward transition from personnel- and costintensive recurring inspections, a.k.a. periodic maintenance, to predictive maintenance. In the work presented; we investigated the application of ultrasonic guided wave propagation to monitor and assess the condition of Type IV composite overwrapped pressure vessel (COPV). A sensor network of fifteen piezo-electric wafers is placed on the carbon fibre reinforced composite cylinder. Five different artificial damage configurations are created by gluing two different weight blocks on three different locations. The database containing measured guided wave data sets is enriched by two different boundary conditions. We utilized an open-source software, openBIS labnotebook, to store and analyse experimental datasets. The guided wave ultrasonic signals were investigated and analysed by using commonly used ultrasonic features (e.g., amplitude, frequency, time of flight) as well as non-traditional time-series features (kurtosis, skewness, variance). The features were used to calculate damage index and the detection performance for the results has been evaluated. The results suggest that both traditional and non-traditional features assume significant importance in artificial damage detection. The future works will additionally involve the impacts of operational conditions, such as periodic pressure variations temperature loadings as well as material degradations.
The application of composite overwrapped pressure vessels (COPV) to store hydrogen and other compressed gases, especially when operating at high pressures, imposed the need for an innovative and reliable approach to ensure the safe operation of the system. Continuous structural health monitoring (SHM) based on ultrasonic guided waves (GWs) is a promising approach due to the ability of the wave to propagate for long distances and go around complex structures, moreover the high sensitivity to various failure modes such as delamination, matrix cracking and debonding. In this study, we scrutinize the behavior of (GWs) within the COPV using a network of PZT elements that are used for excitation and sensing. A laser doppler vibrometer (LDV) was also used to scan the surface of the vessel in various directions. L(0,1) and L(0,2) were observed in the captured signal. The L(0, 2) appeared to be a dominant mode in the COPV and was capable of propagating along the entire length and maintaining a good signal-to-noise ratio. The L(0,2) mode maintained the same phase velocity when it is captured at various excitation angles (0, 45, and 90 degrees). The reduced effect of the orthotropy of the materials on the propagating waves is an important result as it will reduce the complexity in data processing when performing damage identification.
In the event of moisture deterioration, rapid detection and localization is particularly important to prevent further deterioration and costs. For building floors, the layered structure poses a challenging obstacle for most moisture measurement methods. But especially here, layer-specific information on the depth of the water is crucial for efficient and effective repairs. Ground Penetrating Radar (GPR) shows the potential to generate such depth information. Therefore, the present work investigates the suitability of GPR in combination with machine learning methods for the automated classification of the typical deterioration cases (i) dry, (ii) wet insulation, and (iii) wet screed.
First, a literature review was conducted to identify the most common methods for detecting moisture in building materials using GPR. Here, it especially became clear that all publications only investigated individual time-, amplitude- or frequency features separately, without combining them. This was seen as a potential aspect for innovation, as the multivariate application of several signal features can help to overcome individual weaknesses and limitations.
Preliminary investigations carried out on drying screed samples confirmed the profitable use of multivariate evaluations. In addition to the general suitability and dependencies of various features, first limitations due to possible interference between the direct wave and the reflection wave could be identified. This is particularly evident with thin or dry materials, for which the two-way travel times of the reflected radar signals become shorter.
An extensive laboratory experiment was carried out, for which a modular test specimen was designed to enable the variation of the material type and thickness of screed and insulation, as well as the simulation of moisture deteriorations. The data collected revealed clear differences between dry and deteriored structures within measured B-scans. These deviations were to be detected with the newly introduced B-scan features, which evaluate the statistical deviation of A-scan features within a survey line. In this way, deteriorations to unknown floor structures are recognized, regardless of the material parameters present. In a subsequent training and cross-validation process of different classifiers, accuracies of over 88 \% of the 504 recorded measurements (252 different experimental setups) were achieved. For that, the combination of amplitude and frequency features, which covered all relevant reflections of the radar signals, was particularly beneficial. Furthermore, the data set showed only small differences between dry floors and deteriored screeds for the B-scan features, which could be attributed to a homogeneous distribution of the added water in the screeds. The successfully separation of these similar feature distributions raised the suspicion of overfitting, which was examined in more detail by means of a validation with on-site data.
For this purpose, investigations were carried out at five different locations in Germany, using the identical measurement method like in the laboratory. By extracting drilling cores, it was possible to determine the deterioration case for each measurement point and thus generate a corresponding reference. However, numerous data had to be sorted out before classification, since disturbances due to underfloor heating, screed reinforcements, steel beams or missing insulation prevented comparability with the laboratory experiments. Validation of the remaining data (72 B-scans) achieved only low accuracy with 53 \% correctly classified deterioration cases. Here, the previously suspected overfitting of the small decision boundary between dry setups and deteriored screeds within the laboratory proved to be a problem. The generally larger deviations within (also dry) on-site B-scans were thus frequently misclassified as screed deterioration. In addition, there were sometimes strongly varying layer thicknesses or changing cases of deterioration within a survey line, which caused additional errors due to the local limitation of the drilling core reference. Nevertheless, individual on-site examples also showed the promising potential of the applied signal features and the GPR method in general, which partly allowed a profound interpretation of the measurements. However, this interpretation still requires the experience of trained personnel and could not be automated using machine learning with the available database. Nevertheless, such experience and knowledge can be enriched by the findings of this work, which provide the basis for further research.
Future work should aim at building an open GPR data base of on-site moisture measurements on floors to provide a meaningful basis for applying machine learning. Here, referencing is a crucial point, whose limitations with respect to the moisture present and its distribution can easily reduce the potential of such efforts. The combination of several reference methods might help to overcome such limitations. Similarly, a focus on monitoring approaches can also help to reduce numerous unknown variables in moisture measurements and increase confidence in the detection of different deterioration cases.
These data sets serve as models for calculating the specific surface area (BET method) using gas sorption in accordance with ISO 9277.
The present measurements were carried out with nitrogen at 77 Kelvin and argon at 87 Kelvin.
It is recommended to use the following requirements for the molecular cross-sectional area:
Nitrogen: 0.1620 nm²
Argon: 0.1420 nm²
Titanium dioxides certified with nitrogen sorption and additionally measured with argon for research purposes were used as sample material.
The resulting data sets are intended to serve as comparative data for own measurements and show the differences in sorption behaviour and evaluations between nitrogen and argon.
These data are stored in the universal AIF format (adsorption information file), which allows flexible use of the data.
We employ in-house generated synthetic Al-Si matrix composite XCT data for training deep convolutional neural networks for XCT data conditioning and automatic segmentation. We propose an in-house multilevel deep conditioning framework capable of rectifying noise and blur in corrupted XCT data sequentially. Furthermore, for automatic segmentation, we utilize a special in-house network coupled with a novel iterative segmentation algorithm capable of generalized learning from synthetic data. We report a consistent SSIM efficiency of 92%, 99%, and 95% for the combined denoising/deblurring, standalone denoising, and standalone deblurring, respectively. The overall segmentation precision was over 85% according to the Dice coefficient. We used experimental XCT data from various scans of Al-Si matrix composites reinforced with ceramic particles and fibers.
It is shown that preconditioning of experimental X‐ray computed tomography (XCT) data is critical to achieve high‐precision segmentation scores. The challenging experimental XCT datasets and deep convolutional neural networks (DCNNs) are used that are trained with low‐resemblance synthetic XCT data. The material used is a 6‐phase Al–Si metal matrix composite‐reinforced with ceramic fibers and particles. To achieve generalization, in our past studies, specific data augmentation techniques were proposed for the synthetic XCT training data. In addition, two toolsets are devised: (1) special 3D DCNN architecture (3D Triple_UNet), slicing the experimental XCT data from multiple views (MultiView Forwarding), the i.S.Sy.Da.T.A. iterative segmentation algorithm, and (2) nonlocal means (NLM) conditioning (filtering) for the experimental XCT data. This results in good segmentation Dice scores across all phases compared to more standard approaches (i.e., standard UNet architecture, single view slicing, standard single training, and NLM conditioning). Herein, the NLM filter is replaced with the deep conditioning framework BAM SynthCOND introduced in a previous publication, which can be trained with synthetic XCT data. This leads to a significant segmentation precision increase for all phases. The proposed methods are potentially applicable to other materials and imaging techniques.
The applications of composite overwrapped pressure vessels (COPVs) in extreme conditions, such as storing hydrogen gases at very high pressure, impose new requirements related to the system's integrity and safety. The development of a structural health monitoring (SHM) system that allows for continuous monitoring of the COPVs provides rich information about the structural integrity of the component. Furthermore, the collected data can be used for different purposes such as increasing the periodic inspection intervals, providing a remaining lifetime prognosis, and also ensuring optimal operating conditions. Ultimately this information can be complementary to the development of the envisioned digital twin of the monitored COPVs. Guided waves (GWs) are preferred to be used in continuous SHM given their ability to travel in complex structures for long distances. However, obtained GW signals are complex and require advanced processing techniques. Machine learning (ML) is increasingly utilized as the main part of the processing pipeline to automatically detect anomalies in the system's integrity. Hence, in this study, we are scrutinizing the potential of using ML to provide continuous monitoring of COPVs based on ultrasonic GW data. Data is collected from a network of sensors consisting of fifteen Piezoelectric (PZT) wafers that were surface mounted on the COPV. Two ML algorithms are used in the automated evaluation procedure (i) a long short-term memory (LSTM) autoencoder for anomaly detection (defects/impact), and (ii) a convolutional neural network (CNN) model for feature extraction and classification of the artificial damage sizes and locations. Additional data augmentation steps are introduced such as modification and addition of random noise to original signals to enhance the model's robustness to uncertainties. Overall, it was shown that the ML algorithms used were able to detect and classify the simulated damage with high accuracy.
Lanthanide Nanocrystals as Authentication and Security Tags and Reporters for Optical Sensors
(2023)
Counterfeiting of goods has serious economic implications worldwide and can present a considerable threat to human health and national security, rendering product authentication more and more important. This led to an increasing interest in simple tags for anticounterfeiting and authentication applications for the integration into different materials and matrices that are robust enough to survive the respective production processes and can be read out in-situ with simple instrumentation.
Here we present a platform of chemically inert, multi-color luminescent lanthanide nanocrystals (LnNC) consisting of a NaYF4 matrix doped with Yb, Er, Tm, or Ho as promising candidates for such applications.
LnNC with characteristic multi-color emission patterns, composed of narrow bands of varying intensity in the ultraviolet, visible, near-infrared, and short-wave were synthesized via a thermal decomposition approach under inert conditions[1]. The tailor-made design of different emission pattern was achieved by tuning particle size, material composition, and particle surface chemistry in upscaleable syntheses.[2] Particle size and morphology were determined by dynamic light scattering and transmission electron microscopy and the optical properties were characterized by absorption and fluorescence spectroscopy as well as fluorescence lifetime measurements.
The particles were then incorporated into security inks and consumer products. In addition, microenvironment-specific changes in the emission properties of the LnNC tag were utilized to study and sense changes of physico-chemical parameters in different matrices.
Counterfeiting of goods has serious economic implications worldwide and can be a threat to human health and safety. Upconversion nanoparticles (UCNPs)are ideal candidates for optical encoding of various materials. Particles with tailor-made emission patterns can be used as anti-counterfeiting markers and luminophores in security inks and to track material flows. Microenvironment-specific changes in the emission properties of the UCNP tags can be used to study, signal, and sense changes of physico-chemical parameters in different environments, e.g., building
materials.
Demonstrating competency and equivalence for the measurement capacity of contaminants and nutrients in primary foodstuffs is a priority of the OAWG 10-year strategy for Track A core comparisons. Such measurements have posed significant challenges for reference material producers and calibration service providers. This key comparison (KC), under the topic of “non- polar analyte in high carbohydrate food matrix: trans-Zearalenone (trans-ZEN) in maize powder” , was a sector of the model system selected to align with this class within the OAWG strategy. Evidence of successful participation in formal, relevant international comparisons is needed to demonstrate the Calibration and Measurement Capabilities (CMCs) of national metrology institutes (NMIs) and designated institutes (DIs).
17 NMIs and DIs participated in the Track A KC CCQM- 168 “non-polar analyte in high carbohydrate food matrix: trans-ZEN in maize powder” . Participants were requested to evaluate the mass fraction (μg/kg) of trans-ZEN in maize powder material. Methods like liquid-liquid extraction and SPE were applied in the pre-treatment, and HPLC-MS/MS and HPLC-FLD were used for detection by the participants. The mass fractions for trans-ZEN were in the range of (91.8 to 169) μg/kg with standard uncertainties of (1.5 to 24.7) μg/kg, and corresponding relative standard uncertainties from 1.5% to 14.6%. Two labs, INTI and BAM were excluded from the KCRV evaluation. INTI result was identified as an outlier and confirmed their method had insufficient specificity. For BAM the calibration approach they used does not meet the CIPM traceability requirements. The other 15 labs included in the calculation of the consensus KCRV all agreed within their standard uncertainties. Hierarchical Bayes was used as estimators in calculating KCRV and standard uncertainty.
Successful participation in CCQM-K168 demonstrates the measurement capabilities in determining mass fraction of organic compounds, with molecular mass of 100 g/mol to 500 g/mol, having low polarity pKow < -2, in mass fraction range from 1 μg/kg to 1000 μg/kg in a high carbohydrate food matrix.
Trace element (TE) analysis of pyrite via LA-ICP-MS can be used to reconstruct the conditions of pyrite formation in complex mineral systems. The Carpentaria province in northern Australia is host to some of the world’s highest value Zn-Pb (+Ag, Cu) deposits. The genesis of many of these deposits is controversial, with competing models of single-vs. multi-stage ore formation. In this study, LA-ICP-MS data of paragenetically constrained pyrite from the George Fisher Zn-Pb-Ag deposit has been analysed to investigate the chemistry of different stages of ore formation. Pyrite from correlative unmineralized host rocks has also been analysed to investigate evidence of distal hydrothermal anomalism. All LA-ICP-MS data have been statistically evaluated (principal component analysis) and interpreted together with whole rock lithogeochemical data of the same samples. Pre-ore diagenetic pyrite is compositionally similar to other Proterozoic diagenetic pyrite, with some evidence of minor hydrothermal anomalism that with further analysis could help define distal alteration. Pyrite from the different ore stages are compositionally distinct, consistent with a multi-stage system. Ore stage 1 pyrite exceeds background contents of Co, Cu, Zn, As, Ag, Sb, Tl, and Pb and has elevated Co/Ni ratios, whereas only Ni and Co are above background abundances in ore stage 2 and 3 pyrite, of which only ore stage 3 pyrite has high Co/Ni ratios. Ore stage 1 pyrite has a similar composition to hydrothermal pyrite in the undeformed northern Carpentaria CD-type deposits and was likely syn-diagenesis. Ore stage 2 was syn-deformation, and resulted in replacement and recrystallization of pre-existing pyrite, and the expulsion of incompatible TEs. Ore stage 3 formed via a later Cu-Zn-Pb mineralizing event that resulted in a new geochemically distinct generation of Co-rich pyrite. Overall, this study demonstrates the value of paragenetically-constrained pyrite TE data for refining genetic models in complex sediment hosted mineral systems.
AbstractThe minor and trace element composition of minerals provides critical insights into a variety of geological processes. Multi-element mapping by laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS) is an important technique applied for this purpose and although the method is rapidly advancing, there remains a fundamental compromise between spatial resolution, detection limit, and experiment duration when using sequential mass analyzers. To address the limitation of limited analyte selection for high spatial resolution maps imposed by the sequential nature of typical quadrupole (Q)-ICP-MS, we tested the Aerosol Rapid Introduction System (ARIS) for repeat mapping of the same area. The ARIS is a high-speed transfer tubing system that reduces aerosol washout times, permitting resolution of individual pulses at 40–60 Hz. Here, the ARIS was tested not for pulse resolution but with novel operating conditions optimized to perform fast, high spatial resolution mapping of minor and trace element distribution in pyrite and marcasite. For this purpose, ablation was conducted with a 5 µm beam aperture, a repetition rate of 50 Hz, and a continuous stage scan speed of 40 µm s−1. For each LA-Q-ICP-MS map, data were acquired for six elements with an acquisition time of 20 ms per element. This deliberately reduced the individual pulse resolution of the ARIS but instead exploited the spatial resolution and sensitivity gains afforded by the high-laser repetition rate combined with efficient aerosol transfer. The new method successfully mapped trace elements at single to double-digit parts per million levels, and the maps reveal fine-scale zoning of trace elements with an effective x and y resolution of 5 µm, while white light interferometry showed that for each experiment, only ca. 1 µm of the sample was removed. Repeated mapping of the same area showed excellent correspondence not only between element concentrations in successive experiments but also in the shape, dimension, and location of regions of interest defined by concentration criteria. The very good repeatability of the elemental maps indicates that for studies requiring more analytes, successive mapping of additional elements is possible. By contrast with conventional very small spot (i.e., 5 µm) analysis, fast repetition rate and stage scan speed mapping avoids down-hole fractionation effects and minimizes accidental analysis of buried invisible inclusions. Compared to conventional LA-ICP-MS mapping, the method reduces the experiment time by 4–8 times.
Molten sulfur is found in various subaerial volcanoes. However, limited records of the pools and flows of molten sulfur have been reported: therefore, questions remain regarding the physicochemical processes behind this phenomenon. A suite of new sulfur flows, some of which active, was identified at the Lastarria volcano (northern Chile) and studied using satellite imagery, in situ probing, and temperature and video recording. This finding provides a unique opportunity to better understand the emplacement mechanisms and mineral and chemical compositions of molten sulfur, in addition to gaining insight into its origin. Molten sulfur presented temperatures of 124–158°C, with the most prolonged sulfur flow reaching 12 m from the source. Photogrammetric tools permitted the identification of levees and channel structures, with an estimated average flow speed of 0.069 m/s. Field measurements yielded a total volume of 1.45 ± 0.29 m3 of sulfur (equivalent to ∼2.07 tons) mobilized during the January 2019 event for at least 408 min. Solidified sulfur was composed of native sulfur with minor galena and arsenic- and iodine-bearing minerals. Trace element analysis indicated substantial enrichment of Bi, Sb, Sn, Cd, as well as a very high concentration of As (&gt;40.000 ppm). The January 2019 molten sulfur manifestations in Lastarria appear to be more enriched in As compared to the worldwide known volcanoes with molten sulfur records, such as the Shiretoko-Iozan and Poás volcanoes. Furthermore, their rheological properties suggest that the “time of activity” in events such as this could be underestimated as flows in Lastarria have moved significantly slower than previously thought. The origin of molten sulfur is ascribed to the favorable S-rich chemistry of fumarolic gases and changes in host rock permeability (fracture opening). Molten sulfur in Lastarria correlates with a peak in activity characterized by high emissions of SO2 and other acid species, such as HF and HCl, in addition to ground deformation. Consequently, molten sulfur was framed within a period of volcanic unrest in Lastarria, triggered by changes in the magmatic-hydrothermal system. The appearance of molten sulfur is related to physicochemical perturbations inside the volcanic system and is perhaps a precursor of eruptive activity, as observed in the Poás and Turrialba volcanoes.
Use of the solvent-free mechanochemical method for a sustainable preparation of pharmaceuticals
(2023)
With the growing interest in environmental issues on the part of governments and institutions, pharmaceutical industries are asked to reduce their environmental footprint. Given the major impact related to the use of solvents, the development of methodologies less solvent demanding is nowadays even more urgent. In light of that, mechanochemistry would be a suitable solvent-free technology since it promotes the activation of the chemical reactions between (generally) solid materials via inputs of mechanical energy. Since such reactions may occur outside the kinetic and thermodynamic rules of conventional solution chemistry, the main limit of mechanochemistry is the poor mechanistic understanding of the solid-state transformations involved, which is still hindering a widespread use of the method, as well a scale-up to the industrial level. However, the development of methods for real-time monitoring of the mechanochemical reactions enables obtaining (in)accessible information on reaction intermediates, new products, or reaction time, thus getting closer to a better understanding of the mechanistic behaviour. With the rules of this chemistry becoming increasingly clear, the new reaction pathways of mechanochemistry wouldn’t represent a limit anymore, but an asset, that may lead to lot of opportunities for the pharmaceutical industry.
Thermal Destruction of PFAS
(2023)
Thermal treatment processes are currently the only full-scale option for thedestruction of per- and polyfluoroalkyl substances (PFAS) in large waste streams. While all organic molecules including PFAS are susceptible to thermal destruction, their decomposition rates are controlled by process variables such as temperature, reaction atmosphere, and residence time. Concerns exist about the formation of products of incomplete destruction and their emission from hazardous waste incinerators. This talk will summarize the current stateof-the-art of thermal PFAS destruction, identify research needs, and showcase future research designed to address critical knowledge gaps.
The application of compact NMR instruments to continuously flowing samples at higher temperatures or exothermically reacting mixtures is limited by the temperature sensitivity of permanent magnets. Typically, such temperature effects directly influence the achievable magnetic field homogeneity and hence measurement quality. The internal-temperature control loop of the magnet and instruments is typically not designed for compensation of such effects. Passive insulation is restricted by the small dimensions within the magnet borehole.
Here, we present a design approach for active heat shielding with the aim of variable temperature control of NMR samples for benchtop NMR instruments using a compressed airstream which is variable in flow and temperature. Based on the system identification and surface temperature measurements using an optical thermo-graphy setup, a model predictive control was set up to minimize any disturbance effect on the permanent magnet from the probe or sample temperature.
This methodology will facilitate the application of variable-temperature shielding and, therefore, potentially extend the application of compact NMR instruments to flowing samples at higher temperature than the permanent magnet.
The BAMline at the synchrotron X-ray source BESSY II (Berlin, Germany) is supporting researchers especially in materials science. As a non-destructive characterization method, synchrotron X-ray imaging, especially tomography with hard X-Rays, plays an important role in structural 3D characterization. The imaging capabilities allow for in-situ and operando experiments. In this presentation the data handling pipeline is presented.
This report summarizes findings from the first comprehensive study on digitalization in conformity assessment in Africa. The reults are based on data from a survey among conformity assessment bodies (CABs) conducted in 2023. It highlights the digital maturity of the organizations, the motives, benefits and obstacles of digital transformation as well as the actual technology trends.
This study is part of a global project that covers various other countries (see www.qi-fokus.de).
In this paper, we demonstrate the value of 1H NMR relaxometry for studying the hydration of clinker-reduced, more climate-friendly cementitious binders. The results were obtained on typical CEM I cements and sister samples containing two different reactive agricultural ashes as well as non-reactive biochars as supplementary cementitious materials. The findings prove that time-resolved NMR measurements provide valuable additional information when combined with classical heat flow calorimetry.
High polarity analyte(s) in aqueous media: determination of L-PFOA and L-PFOS in ground water
(2022)
The CCQM-K156 comparison was coordinated by TUBITAK UME on behalf of the Organic Analysis Working Group (OAWG) of the Comité Consultatif pour la Quantité de Matière (CCQM) for National Measurement Institutes (NMIs) and Designated Institutes (DIs) which provide measurement services in organic analysis under the 'Comité International des Poids et Mesures' Mutual Recognition Arrangement (CIPM MRA).
Perfluoro alkyl substances (PFAS) such as PFOS and PFOA have been used in numerous industrial applications and products. Because of their high stability and resistance to biodegradation, atmospheric photooxidation, direct photolysis and hydrolysis, they are extremely persistent in the environment. The European Union (EU) Water Framework Directive lists PFOS as a priority hazardous substance that poses a significant risk to the aquatic environment. The use of PFOS-containing Aqueous Film-Forming Foams (AFFFs) has been banned since June 2011 in the EU. As relatively water-soluble, effectively non-degradable compounds, PFOS and PFOA migrate to ground water. They are not removed in the conventional drinking water treatment, and therefore cause health risks in polluted areas. The EU Drinking Water Directive and the European Commission has proposed a limit value of 100 ng/L for the sum of 20 PFAS, including PFOS and PFOA.
This study provides the means for assessing measurement capabilities for determination of high polarity measurands in a procedure that requires extraction, clean-up, analytical separation and detection. Successful participation in CCQM-K156 demonstrates measurement capabilities in determining mass fraction of organic compounds, with a molecular mass of 200 g/mol to 700 g/mol, having high polarity pKow -2, in a mass fraction range from 0.5 ng/kg to 500 ng/kg in aqueous media.
Nine NMIs and DIs participated in the CCQM-K156 key comparison. Seven institutes reported their results. SPE was applied in the sample pre-treatment and LC-MS was applied for detection. All participating laboratories applied isotope dilution mass spectrometry (IDMS) techniques for quantification. Participants established the metrological traceability of their results using certified reference materials (CRMs) from NMIs with stated traceability; where commercially available high purity materials were used the purity was determined in-house. The CCQM-K156 results for L-PFOA and L-PFOS range from 2.75 ng/kg to 5.50 ng/kg with a % RSD of 19.5 % for L-PFOA and from 2.04 ng/kg to 4.45 ng/kg with a % RSD of 21.3 % for L-PFOS. The KCRV was assigned using a Hierarchical Bayesian Random Effects Model (HB REM) estimator from the values reported by six of the participants. One participant result of L-PFOS and one result of L-PFOA were excluded from the KCRV for technical reasons. The KCRV was 4.9 ng/kg ± 0.4 ng/kg for L-PFOA and 3.8 ng/kg ± 0.4 ng/kg for L-PFOS. The six institutes that were included in the assignment of consensus KCRV all agreed within their standard uncertainties.
To reach the main text of this paper, click on Final Report. Note that this text is that which appears in Appendix B of the BIPM key comparison database https://www.bipm.org/kcdb/.
The final report has been peer-reviewed and approved for publication by the CCQM, according to the provisions of the CIPM Mutual Recognition Arrangement (CIPM MRA).
AbstractIn this study, we present a screening method based on molecular absorption spectrometry to study PFAS uptake and fate in plants. To evaluate the suitability of this method we analyzed plant extracts with molecular absorption spectrometry (MAS) as well as liquid chromatography–tandem mass spectrometry (LC–MS/MS) for mass balance studies (w(F)). French bean plants (Phaseolus vulgaris) were grown on soil spiked using eight PFAS substances that vary in chain length and functional group composition. Specifically, these include three short-chained (C4–C5), five long-chained (C7–C10) carboxylic acids, one sulfonic acid and one sulfonic amide moieties. To investigate substance-specific PFAS uptake systematically, PFAS were spiked as single substance spike. Additionally, we studied one mixture of the investigated substances in equal proportions regarding w(F) and four PFAS mixtures of unknown composition. After 6 weeks, the plants were separated into four compartments. We analyzed the four compartments as well as the soil for extractable organically bound fluorine (EOF) by high resolution-continuum source-graphite furnace-molecular absorption spectrometry (HR-CS-GFMAS) as well as for sum of ten target-PFAS by LC–MS/MS. All three short-chained PFAS perfluorobutanoic acid (PFBA), perfluorobutanoic sulfonic acid (PFBS) and perfluoropentanoic acid (PFPeA) were determined in high concentrations mainly in the fruits of the investigated plants while long-chained PFAS perfluorononanoic acid (PFNA) and perfluorodecanoic acid (PFDA) were mainly determined in roots. PFBS was determined in remarkably high concentrations in leaves compartment by both quantification methods. Overall, comprehensive results of single substance spikes were in good agreement for both methods except for a few cases. Hence, two phenomena were identified: for mixed PFAS spikes of unknown composition huge differences between EOF and sum of target PFAS were observed with systematically higher EOF values. Overall, both methods indicate comparable results with MS being more reliable for known PFAS contamination and MAS being more valuable to identify PFAS exposure of unknown composition.
Graphical Abstract
The lack of traceability to meter of X-ray Computed Tomography (CT) measurements still hinders a more extensive acceptance of CT in coordinate metrology and industry. To ensure traceable, reliable, and accurate measurements, the determination of the task-specific measurement uncertainty is necessary. The German guideline VDI/VDE 2630 part 2.1 describes a procedure to determine the measurement uncertainty for CT experimentally by conducting several repeated measurements with a calibrated test specimen. However, this experimental procedure is cost and effort intensive. Therefore, the simulation of dimensional measurement tasks conducted with X-ray computed tomography can close these drawbacks. Additionally, recent developments towards a resource and cost-efficient production (“smart factory”) motivate the need for a corresponding numerical model of a CT system (“digital twin”) as well. As there is no standardized procedure to determine the measurement uncertainty of a CT system by simulation at the moment, the project series CTSimU was initiated, aiming at this gap. Concretely, the goal is the development of a procedure to determine the measurement uncertainty numerically by radiographic simulation. The first project (2019-2022), "Radiographic Computed Tomography Simulation for Measurement Uncertainty Evaluation - CTSimU" developed a framework to qualify a radiographic simulation software concerning the correct simulation of physical laws and functionalities. The most important outcome was a draft for a new guideline VDI/VDE 2630 part 2.2, which is currently under discussion in the VDI/VDE committee. The follow-up project CTSimU2 "Realistic Simulation of real CT systems with a basic-qualified Simulation Software" will deal with building and characterizing a digital replica of a specific real-world CT system. The two main targets of this project will be a toolbox including methods and procedures to configure a realistic CT system simulation and to develop tests to check if this replica is sufficient enough. The result will be a draft for a follow-up VDI/VDE guideline proposing standardized procedures to determine a CT system's corresponding characteristics and test the simulation (copy) of a real-world CT system which we call a "digital twin".
Referenzmaterialien sind unter anderem ein wichtiges Werkzeug zur Qualitätskontrolle von Messungen bestimmter Merkmalswerte. Dabei ist zu berücksichtigen, dass zertifizierte Merkmalswerte immer eine gewisse Unsicherheit haben. Die Ermittlung dieser Unsicherheitsbeiträge ist Gegenstand des Vortrags. Referenzmaterialien sind gleichzeitig ein wertvolles Werkzeug zur Ermittlung der Unsicherheit von Messverfahren und -Analysen unbekannter Proben. Die Vorgehensweise bei der Ermittlung der Messunsicherheit mit Hilfe eines Referenzmaterials wird beschrieben.
An introductory lecture on the Dark Side of Science; what it is, why it exists, and what can be done to fight it. This lecture illuminates the increasing prevalence of fraudulent scientific work (e.g. faked data, manipulated images, paper mills) with plenty of examples and sources. The second section expands on the driving forces that caused this phenomenon to emerge, largely driven by pressures from management, peers and the researcher themselves. The third section expands on methods and tools that can be used to educate and arm oneself against this phenomenon. The 2023 edition includes new examples of larger fraudulent bodies of work emerging, and the problems posed by the arrival of LLMs.
The project series CTSimU was initiated with the goal to develop a set of procedures to enable the determination of the task-specific measurement uncertainty of a CT system numerically by radiographic simulation. The first project (2019-2022) “Radiographic Computed Tomography Simulation for Measurement Uncertainty Evaluation - CTSimU” was focused on the sufficient physical correctness of the radiographic simulation and created as a result a test framework for simulation softwares and a draft of a VDI standard in the series VDI/VDE 2630 for this application. However, for the realistic simulation of a CT system in a simulation software (i.e. a digital twin), not only the correctness of the simulation software itself is crucial, but also the quality of the parameterization of the CT system in the simulation software - this represents the starting point of the 2nd project “Realistic Simulation of real CT systems with a basic-qualified Simulation Software - CTSimU2” (2022-2024).
The parameterization of a CT system in a simulation software can be divided into four steps: after the data acquisition at the real CT system (step 1) follows the evaluation of the acquired data for the generation of general parameter specifications (step 2). It follows the transfer of the parameters into the specific simulation software (step 3) and the validation of the resulting simulation parameters by a suitable test (step 4). The intended result of the project CTSimU2 is a draft VDI standard (for VDI/VDE 2630) for this test, which contains an informative annex on the state of the art regarding the possibilities for parameter determination.
The possibility of obtaining high-purity, isotopically modified and nanostructured elemental substances 29Si, 98Mo, and 100Mo, as well as 98Mox10By compounds from volatile halides under conditions of laser optical breakdown of a pulsed Nd:YAG laser is shown. Currently, research in the field of developing new methods for obtaining high-purity, isotopically modified and nanostructured substances is being actively conducted. Interest in Si and Mo combining these forms has noticeably increased. In nuclear medicine, 29Si-enriched nanoparticles can be used as contrast agents in magnetic resonance imaging (MRI), and 98Mo and 100Mo isotopes can be used to obtain the unstable 99mTc radioisotope. These applications do not require large amounts of isotopically modified Si and Mo. Their obtaining belongs to the problems of small chemistry. When obtaining isotopically modified Si and Mo, it is expedient to use their volatile fluorides, for which technologies of isotope enrichment and deep purification are well developed. These halides have high chemical and thermal stability; therefore, plasma-chemical methods based on the plasma of a pulsed discharge generated by laser breakdown can be promising for separating 29Si, 98Mo, and 100Mo from them. Laser breakdown in H2+Ar+SiF4 and H2+Ar+MoF6 mixtures in various stoichiometric ratios in the pressure range 30–760 Torr was carried out using a pulsed Nd:YAG laser. The pulse duration at a wavelength of 1064 nm was 15 ns, the repetition rate was 5 Hz. A pulse energy of 800 mJ was focused by a lens with a focal length of 5 cm. The energy density at the focus was 26 J/cm3 . It has been shown that when using a mixture based on 29SiF4, the sample contains a 29Si crystalline phase with an average grain size of 30–50 nm (Fig. 1a). When using a mixture based on 98MoF6, the sample contains a 98Mo crystalline phase with an average grain size of 70–100 nm (Fig. 1b). In this type of gas discharge, the possibility of forming superhard materials, isotopically modified molybdenum borides, was also studied. These substances in the form of nanosized particles have improved tribological properties. After ablation of metallic Mo in the H2 + BF3 mixture, the main phase was MoB2 in the form of a nanodispersed powder with an average grain size of 100 nm (Fig. 1c) [1]. A technique for modeling gas-dynamic and thermal conditions in a low-temperature chemically active plasma induced by laser breakdown is proposed. Using computational experiments, the features of gas mixture heating and the formation of nanoparticles in the LIBS reactor were studied
Virtual CT with aRTist
(2023)
The software aRTist is a simulation tool for the generation of realistic radiographs of virtual radiographic superstructures.
With radiographic simulations, virtual component models can be scanned as in a computer tomograph.
Industrial X-ray computed tomography (CT) enables the non-destructive detection of internal and external surfaces as well as inhomogeneities of technical objects. Virtual CT offers new possibilities for the investigation of parameter influences of this complex testing and measuring technique. In addition to the option of switching physical effects on and off, scanning movements can also be tested before their technical realization.
The virtual CT generates projection images from different directions for the subsequent reconstruction of a volume model of the examined object. The reconstruction of the simulated scans is carried out with the algorithms and programs for real scans. Tomographic scans consist of a large number of projections, which practically cannot be generated individually by the user of a simulation. The software offers various options for the automated simulation of tomographic scans. These range from standard CT to scans on free trajectories or with individual projection matrices.
Interest in the type of skin used in scriptural materials and preparation methods increased from the nineteenth into the twentieth century. This was due partly to the number of newly discovered fragments and to the invention of new instruments and scientific procedures to identify animal skins and produce qualitative means to demonstrate specific preparation reagents and techniques. The invention of various means of analyzing the DNA of organic materials brought about a revolution in archaeology and in conservation. Difficulties in overcoming contamination of archaeological samples resulted in a number of controversies but also produced advances and improvement in the techniques of ancient DNA analysis and interpretation of results.
Physico-chemical analyses of writing materials offer insight into various questions associated with historical, cultural, and conservational aspects of manuscript studies. The catalogue of questions that can be addressed with these methods includes authenticity, dating, the attribution of various parts of the text to different scribes and the relation between the primary and secondary texts. Similarly, preservation of the manuscripts requires knowledge of the composition of the original materials versus old repairs, identification of damage, as well as recognition of natural aging and degradation processes. The material sciences can contribute data about the chemical compositions of the writing materials, elucidation of the techniques of their production and the absolute age of organic components, as well as characterization of corrosion effects, evaluation of conservation treatment, and monitoring of the preservation state.
The processes of hydrogen reduction of silicon and germanium chlorides under the conditions of radio-frequency (40.68 MHz) counteracted arc discharge stabilized between two rod electrodes were investigated. The main gas-phase and solid products of plasma-chemical transformations were determined.
Thermodynamic analysis of SiCl4 + H2 and GeCl4 + H2 systems was carried out. It is shown that under the implemented experimental conditions, equilibrium components of the products are established. The detected spectra of chemical activity were studied, which gave reason to assume that the molecular mechanism of the hydrogen reduction process is the main one. The impurity composition of gas-phase and solid reaction products was investigated. The possibility of single-stage production of high-purity Si and Ge mainly in the form of compact ingots, as well as high-purity chlorosilanes and trichlorogermane, was shown.
Ergot alkaloids are a group of toxic compounds, formed by fungi on infested grasses. In 2022, the European Commission set into effect maximum levels for the sum of the twelve major ergot alkaloids in multiple foods. To facilitate the laborious and costly individual quantification of the twelve major ergot alkaloids by HPLC–MS/MS or -FLD, we recently reported a sum parameter method (SPM) for ergot alkaloid quantification. Here, derivatization to lysergic acid hydrazide—a derivative of the mutual ergoline backbone in all ergot alkaloids—allowed simplified determination of all ergot alkaloids in flour via HPLC-FLD. For the measurement of more complex matrices like processed foods, we now developed a MS/MS-based SPM. Two internal standards (IS), isotopically labelled at different positions of the molecule, were synthesized and employed in the MS/MS-measurements. Method performance using either the 13CD3-labelled or the 15N2-labelled IS was evaluated on naturally contaminated rye and wheat flour samples as well as on processed food matrices. Employing the 13CD3-labelled IS leads to lower variances and better consistency with the reference data (obtained by the FLD-based SPM) in flour samples compared to the 15N2-labelled IS. The novel method significantly improves the measurement of ergot alkaloids in complex food matrices, due to their increased selectivity and thus lower interferences. Furthermore, the application of isotope labelled IS obviates the need for time-consuming steps like the determination of recovery rate based, matrix specific correction factors as described in the MS/MS-based European standard method for ergot alkaloid quantification (EN 17425).
Research into new sources for EUV lithography is driving advancements in experimental methods tailored for this short wavelength range. This progress enables the exploration of spectroscopic techniques aimed at monitoring electronic transitions within this energy spectrum. Laser-induced breakdown spectroscopy (LIBS) serves as a rapid tool for elemental analysis, primarily established in the UV-vis range. However, LIBS encounters challenges such as limited repeatability precision and elevated background noise resulting from continuum radiation.
In parallel, laser-induced extreme UV spectroscopy (LIXS) delves into the initial stages of plasma evolution, characterized by the emergence of soft X-ray and extreme UV radiation. The method benefits from a fast timeframe and constrained plasma confinement, leading to better precision. Nevertheless, LIXS encounters convoluted spectra arising from unresolved transition arrays (UTA), particularly pronounced for heavier elements. This complexity renders conventional univariate data analysis impractical, demanding the adoption of a multivariate data analysis approach.
Multiple cathode samples, each coated with varying stoichiometries of lithium nickel manganese cobalt oxide (NMC), were prepared and used for calibration purposes. Through the application of Partial Least Squares (PLS) regression, a robust correlation with an R2 value exceeding 0.97 was achieved. The LIXS technique underwent a comparative evaluation against UV-vis LIBS. Furthermore, a comparison between univariate and multivariate analysis approaches was conducted, incorporating validation through y-randomization to mitigate overfitting risks.
The viability of this approach was confirmed through the testing of an NMC reference material. The results showed metrological compatibility with reference values, underscoring the potential capability of the proposed methodology.
Laser-based active thermography is a contactless non-destructive testing method to detect material defects by heating the object and measuring its temperature increase with an infrared camera. Systematic deviations from predicted behavior provide insight into the inner structure of the object. However, its resolution in resolving internal structures is limited due to the diffusive nature of heat diffusion. Thermographic super resolution (SR) methods aim to overcome this limitation by combining multiple thermographic measurements and mathematical optimization algorithms to improve the defect reconstruction.
Thermographic SR reconstruction methods involve measuring the temperature change in an object under test (OuT) heated with multiple different spatially structured illuminations. Subsequently, these measurements are inputted into a severely ill-posed and heavily regularized inverse problem, producing a sparse map of the OuT’s internal defect structure. Solving this inverse problem relies on limited priors, such as defect-sparsity, and iterative numerical minimization techniques. Previously mostly experimentally limited to one-dimensional regions of interest (ROIs), this thesis aims to extend the method to the reconstruction of two-dimensionalROIs with arbitrary defect distributions while maintaining reasonable experimental complexity. Ultimately, the goal of this thesis is to make the method suitable for a technology transfer to industrial applications by advancing its technology readiness level (TRL).
In order to achieve the aforementioned goal, this thesis discusses the numerical expansion of a thermographic SR reconstruction method and introduces two novel algorithms to invert the underlying inverse problem. Furthermore, a forward solution to the inverse problem in terms of the applied SR reconstruction model is set up. In conjunction with an additionally proposed algorithm for the automated determination of a set of (optimal) regularization parameters, both create the possibility to conduct analytical simulations to characterize the influence of the experimental parameters on the achievable reconstruction quality. On the experimental side, the method is upgraded to deal with two-dimensional ROIs, and multiple measurement campaigns are performed to validate the proposed inversion algorithms, forward solution and two exemplary analytical studies. For the experimental implementation of the method, the use of a laser-coupled DLP-projector is introduced, which allows projecting binary pixel
patterns that cover the whole ROI, reducing the number of necessary measurements per ROI significantly (up to 20x).
Finally, the achieved reconstruction of the internal defect structure of a purpose-made OuT is qualitatively and qualitatively benchmarked against well-established thermographic testing methods based on homogeneous illumination of the ROI. Here, the background-noise-free two-dimensional photothermal SR reconstruction results show to outclass all defect reconstructions by the considered reference methods.
The overview of the activity of Federal Institute for Material Research and Testing (BAM, Belin, Germany) in the field of additively manufacturing material characterization will be presented. The research of our group is focused on the 3D imaging of AM materials by means of X-ray Computed Tomography at the lab and at synchrotron, and the residual stress characterization by diffraction (nondestructive technique). Also, two successful research project in collaboration with CAM2, Sweden are presented.
Gold-based nanoparticles below 2 nm in size are promising as luminescent probes for in vivo bioimaging, owing to their brightness and rapid renal clearance. However, their use as contrast agents in the near-infrared II (NIR-II, 1000–1700 nm) range remains challenging due to their low photoluminescence (PL) quantum yield. To address this, PL enhancement can be achieved by either rigidifying the ligand-shell structure or increasing the size of the ligand shell. In this study, we synthesized ultra-small gold nanoparticles stabilized by co-ligands, namely monothiol and short dithiol molecules. By precisely controlling the amount of reducing agent used during particle preparation, we successfully modulated the physicochemical properties of the co-ligand shell, including its size, composition, and structure. Consequently, we achieved a remarkable 60-fold increase in the absorption cross-section at 990 nm while maintaining the small size of the 1.5-nm metal core. The analytical and optical characterization of our thiol-capped gold nanoparticles indicates that the ligand shell size is governed by the quantity of the reducing agent, which, in turn, impacts the balance between radiative and non-radiative processes, thereby influencing the PL quantum yield.
Tailor-made nanoparticles are of increasing interest in e.g. catalysis, as sensor materials, analytical assays, or can have superior photophysical properties. A major issue concerning the preparation of high-quality and functional nanoparticles is a good control of particle size, shape, polydispersity, and composition.
Small Angle X-ray Scattering (SAXS) is a non-destructive method for the analysis of nanostructures in a wide variety of materials. This method allows determining averaged structural parameters on a length scale from just above atomic sizes up to several 100 nanometers such as sizes, size distributions, volume fractions, and inner surface sizes. Moreover, anomalous Small Angle X-ray Scattering (ASAXS) exploits the anomalous dispersion of the scattering amplitudes near the X-ray absorption edges of the elements contained in the sample. These element sensitive contrast variations can be used to analyse average composition fluctuations on the nm scale. Two kinds of nanoparticles are chosen here to elaborate the advantages of ASAXS in the analysis of complex materials.
A facile and efficient methodology is developed for the thermal synthesis of size-tunable, stable, and uniform bimetallic NiCu core–shell nanoparticles (NPs) for various application in catalysis. Their diameter can be tuned in a range from 6 nm to 30 nm and the Ni:Cu ratio is adjustable in a wide range from 1:1 to 30:1. The NPs are structurally characterized by a method combination of transmission electron microscopy, anomalous small-angle X-ray scattering (ASAXS), X-ray absorption fine structure, and X-ray photoelectron spectroscopy. Here, we focus on the ASAXS method and its ability to analyses nanostructure parts and their compositions at once. As a result, a NiCu alloyed core surrounded by a Ni enriched shell and an outer NiO shell was found.
Semiconductor nanocrystals (quantum dots, QDs) are well known for their superior photophysical properties and enabled advancements in several key technologies of the 21st century and numerous technological applications like in photovoltaics, LED displays, photocatalysis, and biosensing. To achieve high photoluminescence quantum yields (PLQY) and enhanced photostability the QD core needs to be passivated by a second semiconductor, which possess a larger band gap to confine the charges within the QD core. An important parameter is thereby the lattice mismatch between the core and shell. To avoid strong lattice strain, which would alter the photophysical properties, an intermediary shell can be used as a lattice adapter between the core and the outer shell leading to core/shell/shell systems. These systems have shown to possess high PLQYs combined with a strong long-term stability and can be found in modern QLED displays. ASAXS was used here to better understand the core/shell/shell structure of InP/ZnSe/ZnS QDs to enable a correlation between their structural and photophysical properties.
Detaillierte Kenntnisse der elastischen Materialeigenschaften sind in vielen ingenieurtechnischen Bereichen von grundlegender Bedeutung. Insbesondere für die Anwendung von Predictive Maintenance und Structural- Health-Monitoring Methoden mit Ultraschall ist die genaue Kenntnis der elastischen Materialkonstanten eine Grundvoraussetzung. Die von den Herstellern zur Verfügung gestellten Angaben zu den elastischen Materialkonstanten, insbesondere für Polymere und faserverstärkte Kunststoffe, sind jedoch oft unzureichend, da diese vom Produktionsprozess abhängig sind und sich zusätzlich aufgrund von Materialabbauprozessen oder Ermüdung ändern können. In der Praxis liegen polymere Werkstoffe, faserverstärkte Kunststoffe und Metalle oft als dünne, plattenförmige Strukturen vor, in welchen sich geführte Ultraschallwellen (UGWs) ausbreiten können. In der aktuellen Forschung sind bereits verschiedene Neuronale Modelle zur Bestimmung der elastischen Konstanten und der Materialcharakterisierung mittels UGWs bekannt. Ein einfaches neuronales Netz, mit aus Dispersionsbildern extrahierten Werten für Frequenz und Wellenzahl ausbeutungsfähiger Moden als Eingabe, zur Vorhersage der elastischen Konstanten wird in verwendet. Ein rekurrentes Neuronales Netz mit einem Zeit-Frequenz Vektor als Eingabe wird in angewandt, während in ein 1D- Convolutional-Neuronal-Networks (CNN) unter Verwendung der zeitlichen Auslenkung der Grundmoden und in ein 2D-CNN unter Verwendung einer polaren Gruppengeschwindigkeitsdarstellung zur Bestimmung der elastischen Konstanten verwendet wird. In diesem Vortrag wird ein Ansatz zur Bestimmung der isotropen elastischen Konstanten von dünnen Platten auf der Grundlage von UGWs unter Verwendung von Dispersionsbildern und 2D-CNNs vorgestellt. Dispersionsabbildungen aus numerischen Simulationen werden mithilfe verschiedener Methoden vorverarbeitet, um realistische Messdaten zu simulieren. Mit den modifizierten Daten wird das Modell trainiert und die Architektur optimiert. Anschließend wird die Genauigkeit des erzeugten Modells mit realen Messdaten validiert. Es wird gezeigt, dass 2D-CNNs in der Lage sind, die isotropen elastischen Konstanten anhand multimodaler Merkmale aus Dispersionsbildern vorherzusagen, ohne dass eine anfängliche Schätzung der Parameter oder manuelle Merkmalsextraktion erforderlich ist.
This paper presents an automatic damage imaging technique by employing a signal processing approach based on applying hierarchically clustered filters across different domains. The technique involves time-frequency-wavenumber filter banks which are applied sequentially to ultrasonic guided wave (UGW) data. The study is conducted for a single lap joint composite specimen with a special focus on small voids which were formed due to manual adhesive component mixing. UGW data are acquired with a 3D Scanning Laser Doppler Vibrometer (LDV) over the scan area of the bonded plate. UGWs are excited at the central frequency of 100 kHz by a single piezoelectric transducer mounted on the surface of the single plate. Within each domain of time, frequency, and wavenumber, four filters are designed which results in 64 distinct filtered wavefields. From each filtered wavefield, an image is obtained by using root-mean-square (RMS) calculation of the signals. The obtained results are then combined to create a final, improved-resolution image of the scan area. The final image is compared to the image obtained through RMS calculation of full wavefield with interpolation through Delaunay triangulation and the image obtained by X-ray radiography. The results show that the smallest void that could be detected has a diameter of 2.14 mm.
Fungal pigments such as melanin and carotenoids are distinctive markers of animal and plant pathogenic fungi as well as their environmental relatives. These complex pigments play important roles in pathogenicity and stress tolerance while also being useful as biomarkers. Accordingly, it is important to be able to identify in situ the pigments in black fungi, a group of clinical and environmental importance. In this study, wild-type and genetically modified strains of Knufia petricola A95 and wild fungal cells attached to ancient rock were investigated for their spectroscopic and microscopic Raman features and morphological appearance. Knockout mutants of melanin synthesis genes pks1 (polyketide synthase), sdh1 (scytalone dehydratase), and both pks1 and the carotenoid synthesis gene phd1 (phytoene desaturase) were studied We applied two different Raman microscopes using two lasers, with 633 nm and 488 nm wavelengths. We analyzed and compared Raman spectra between the measured reference substances and the mutant and wild-type strains. In the wild strain WT:A95, the peaks close to melanin peals were found at 1353 cm−1 and 1611 cm−1. There are no characteristic melanin peaks at 1580–1600 cm−1 and around 1350 cm−1 at the spectrum of the Δpks1/Δphd1 mutant and the Δsdh1 mutant. The Δpks1 mutant spectrum has the peaks at the beta-carotene v2 C-C in-plane stretch at 1155 cm−1 and v3 C-CH3 deformation at 1005 cm−1. The peaks of carotenoids and melanin were found in all mutants and the wild strain, except the Δpks1/Δphd1 mutant. Raman spectra allow for discrimination between the various pigments. Hence, interactions between natural fungal melanin, as well as other protective pigments, and complex environmental matrices can be characterized on a range of spatial and temporal scales.
BAM (Federal Institute for Materials Research and Testing) is developing an electronic measurement system to be placed inside a waste drum, which will be filled with concrete. The goal of this measurement system is to monitor the process of hardening and the evolution of the concrete itself over time to indirectly identify potential defects such as corrosion or cracking. The measured parameters are humidity, temperature, and pressure. In this regard, particular attention was given to the design of the electronic board’s enclosure, to allow the sensors to measure the state of the concrete without being in direct contact with it. In the scope of the European Commission’s project of PREDIS, the supply of power to the battery-less sensors and the data acquired by such sensors are transmitted through the metallic waste drum by an innovative wireless technology developed by VTT (Technical Research Centre of Finland) in order to ensure long-term operation while keeping the integrity of the sealed container.
BAM is developing an electronic measurement system to be placed inside a waste drum, which will be filled with concrete. The goal of this measurement system is to monitor the process of hardening and the evolution of the concrete itself over time to indirectly identify potential defects such as corrosion or cracking. The measured parameters are humidity, temperature, and pressure. In this regard, particular attention was given to the design of the electronic board’s enclosure, to allow the sensors to measure the state of the concrete without being in direct contact with it. In the scope of the EU project PREDIS, the data acquired by such sensors are transmitted from inside to outside the metallic waste drum through wireless technology.
The sensing system is made of a chain of small sensing units, called SensorNodes. Each SensorNode includes two off-the-shelf sensors, one for relative humidity and temperature and one for pressure and temperature. A SensorNode is designed to have a unique identifier, in order to be connected to other units while being uniquely discoverable by a standard communication protocol. In this way, a distributed matrix of measurement points is created.
One of the most challenging tasks in designing a measurement system to run in a harsh environment (such as hardening concrete) is to let the sensors sense the external environment without damaging the sensor itself.
To keep the external environment away from the electronic board while still letting the sensors measure the concrete behavior, holes have been drilled through the lid and covered from the inside with a layer of a porous membrane. The membrane's pores allow water and gas particles to pass through and let the enclosed air equilibrate with the external environment.
With the help of the developed sensors, monitoring concrete in cemented waste drums will be possible. The derived data will also serve as the basis for ongoing modeling approaches for digital twins within the Predis project. Overall, the sensors provide a means of enabling safe nuclear waste management through advanced monitoring
Research on per- and polyfluoroalkyl substances (PFAS) frequently incorporates organofluorine measurements, particularly because they could support a class-based approach to regulation. However, standardized methods for organofluorine analysis in a broad suite of matrices are currently unavailable, including a method for extractable organofluorine (EOF) measured using combustion ion chromatography (CIC). Here, we report the results of an international interlaboratory comparison. Seven laboratories representing academia, government, and the private sector measured paired EOF and PFAS concentrations in groundwater and eel (Anguilla rostrata) from a site contaminated by aqueous film-forming foam. Among all laboratories, targeted PFAS could not explain all EOF in groundwater but accounted for most EOF in eel. EOF results from all laboratories for at least one replicate extract fell within one standard deviation of the interlaboratory mean for groundwater and five out of seven laboratories for eel. PFAS spike mixture recoveries for EOF measurements in groundwater and eel were close to the criterion (±30%) for standardized targeted PFAS methods. Instrumental operation of the CIC such as replicate sample injections was a major source of measurement uncertainty. Blank contamination and incomplete inorganic fluorine removal may introduce additional uncertainties. To elucidate the presence of unknown organofluorine using paired EOF and PFAS measurements, we recommend that analysts carefully consider confounding methodological uncertainties such as differences in precision between measurements, data processing steps such as blank subtraction and replicate analyses, and the relative recoveries of PFAS and other fluorine compounds.
Laser-based active thermography is a contactless non-destructive testing method to detect material defects by heating the object and measuring its temperature increase with an infrared camera. Systematic deviations from predicted behavior provide insight into the inner structure of the object. However, its resolution in resolving internal structures is limited due to the diffusive nature of heat diffusion. Thermographic super resolution (SR) methods aim to overcome this limitation by combining multiple thermographic measurements and mathematical optimization algorithms to improve the defect reconstruction.
Thermographic SR reconstruction methods involve measuring the temperature change in an object under test (OuT) heated with multiple different spatially structured illuminations. Subsequently, these measurements are inputted into a severely ill-posed and heavily regularized inverse problem, producing a sparse map of the OuT’s internal defect structure. Solving this inverse problem relies on limited priors, such as defect-sparsity, and iterative numerical minimization techniques. Previously mostly experimentally limited to one-dimensional regions of interest (ROIs), this thesis aims to extend the method to the reconstruction of twodimensional ROIs with arbitrary defect distributions while maintaining reasonable experimental complexity. Ultimately, the goal of this thesis is to make the method suitable for a technology transfer to industrial applications by advancing its technology readiness level (TRL).
In order to achieve the aforementioned goal, this thesis discusses the numerical expansion of a thermographic SR reconstruction method and introduces two novel algorithms to invert the underlying inverse problem. Furthermore, a forward solution to the inverse problem in terms of the applied SR reconstruction model is set up. In conjunction with an additionally proposed
algorithm for the automated determination of a set of (optimal) regularization parameters, both create the possibility to conduct analytical simulations to characterize the influence of the experimental parameters on the achievable reconstruction quality. On the experimental side, the method is upgraded to deal with two-dimensional ROIs, and multiple measurement campaigns are performed to validate the proposed inversion algorithms, forward solution
and two exemplary analytical studies. For the experimental implementation of the method, the use of a laser-coupled DLP-projector is introduced, which allows projecting binary pixel patterns that cover the whole ROI, reducing the number of necessary measurements per ROI significantly (up to 20x).
Finally, the achieved reconstruction of the internal defect structure of a purpose-made OuT is qualitatively and qualitatively benchmarked against well-established thermographic testing methods based on homogeneous illumination of the ROI. Here, the background-noise-free twodimensional photothermal SR reconstruction results show to outclass all defect reconstructions by the considered reference methods.
X-ray photoelectron-spectroscopy (XPS) allows simultaneous irradiation and damage monitoring. Although water radiolysis is essential for radiation damage, all previous XPS studies were performed in vacuum. Here we present near-ambient-pressure XPS experiments to directly measure DNA damage under water atmosphere. They permit in-situ monitoring of the effects of radicals on fully hydrated double-stranded DNA. Our results allow us to distinguish direct damage, by photons and secondary low-energy electrons (LEE), from damage by hydroxyl radicals or hydration induced modifications of damage pathways. The exposure of dry DNA to x-rays leads to strand-breaks at the sugar-phosphate backbone, while deoxyribose and nucleobases are less affected. In contrast, a strong increase of DNA damage is observed in water, where OH-radicals are produced. In consequence, base damage and base release become predominant, even though the number of strand-breaks increases further. Furthermore, first data about the degradation of single-stranded DNA binding-proteins (G5P / GV5 and hmtSSB) under vacuum and NAP-XPS conditions are presented.
We give an overview about recent work concerning ionizing radiation damage to Oligonucleotides, plasmid DNA, DNA binding proteins (G5P), and DNA-protein complexes.
We focus on combining new experimental setups with Geant4/TOPAS particle scattering simulations to understand the effets of ionizing radiation.
Radiation biophysics
(2023)
A round-robin study has been carried out to estimate the impact of the human element in small-angle scattering data analysis. Four corrected datasets were provided to participants ready for analysis. All datasets were measured on samples containing spherical scatterers, with two datasets in dilute dispersions and two from powders. Most of the 46 participants correctly identified the number of populations in the dilute dispersions, with half of the population mean entries within 1.5% and half of the population width entries within 40%. Due to the added complexity of the structure factor, far fewer people submitted answers on the powder datasets. For those that did, half of the entries for the means and widths were within 44 and 86%, respectively. This round-robin experiment highlights several causes for the discrepancies, for which solutions are proposed.
Inputs of plastic impurities into the environment via the application of fertilizers are regulated in Germany and the EU by means of ordinances. Robust and fast analytical methods are the basis of legal regulations. Currently, only macro- and large microplastic contents (>1 mm) are measured. Microplastics (1–1,000 µm), are not yet monitored. Thermal analytical methods are suitable for this purpose, which can determine the mass content and can also be operated fully automatically in routine mode. Thermal extraction desorption-gas chromatography/mass spectrometry (TED-GC/MS) allows the identification of polymers and the determination of mass contents in solid samples from natural environments. In accordance with the German or European Commission (EC) Fertiliser Ordinance, composting plants should be monitored for microplastic particles with this method in the future. In this context a compost plant was sampled. At the end of the rotting process, the compost was sieved and separated in a coarse (>1 mm) and a fine fraction (<1 mm). The fine fraction was processed using density separation comparing NaCl and NaI as possible salt alternative and screened for microplastic masses by TED-GC/MS with additional validation and quality assurance experiments. With TED-GC/MS total microplastics mass contents of 1.1–3.0 μg/mg in finished compost could be detected with polyethylene mainly. What differs much to the total mass of plastics in the coarse fraction with up to 60 μg/mg, which were visually searched, identified via ATR-FTIR and gravimetrically weighted.
In the course of tomorrow's hydrogen-based energy transition, the construction of the corresponding infrastructure will play a central role. The majority of materials used to date are typically welded for component fabrication. In that context, steels are widely applied and can be prone to hydrogen embrittlement. This includes the classical delayed cold cracking during welding processing as well as embrittlement phenomena during operation. For the evaluation of any hydrogen effect on, for example, the mechanical properties of a welded metallic material, the hydrogen content must be precisely determined. In the case of welds, for example, according to ISO 3690, this is the isothermal carrier gas hot extraction (CGHE). CGHE is based on accelerated hydrogen degassing due to thermal activation of hydrogen at elevated temperatures. In addition to the pure quantification of hydrogen, thermal desorption analysis (TDA) with varied heating rates can be used to determine and evaluate the bonding state at microstructural defects in the material. For both techniques, experimental and measurement influences have to be considered, which have a great effect on the result. For CGHE, for example, ISO 3690 suggests different sample geometries as well as minimum extraction times. The present study summarizes results and experiences of numerous investigations with different sample temperatures and geometries (ISO 3690 type B and cylindrical TDA samples) regarding: the influence of the sample surface (polished/welded), measurement accuracies depending on the sample volume as well as the insufficient monitoring of the effect of the PI controller on the extraction temperature. In particular, a deviating extraction temperature to the set temperature, can significantly falsify the measurement results. Based on the results, methods are shown to quickly reach the desired extraction temperature without having to physically interfere with the measurement equipment. This serves to substantially improve the reliability of hydrogen measurement through increased signal stability and accelerated hydrogen desorption. In general, an independent temperature measurement with dummy samples for the selected heating procedure is advisable to exclude possible unwanted temperature influences already before the measurement. In addition (and way more important), the methods described can be transferred directly to industrial applications.
Multi-principal element alloys (MPEAs) are innovative materials that have attracted extensive research attention within the last decade. MPEAs are characterized by a solid solution of equiatomic metallic elements. Depending on the number of elements, they are also referred as high entropy alloys (HEAs with n ≥ 4 elements like CoCrFeMnNi) and medium-entropy alloys (MEA with n = 3 elements CoCrNi). Depending on the alloy concept, MPEAs show exceptional properties in terms of mechanical performance or corrosion resistance at extreme environments. In that connection, hydrogen and its challenges for the most metallic materials gets more and more important. MPEAs are candidate materials for the substitution of conventional materials like austenitic stainless steels e.g., at very high-pressure up to 1000 bar. Those pressures are typically reached in valves or compressors for refueling of tanks with operational pressure of 700 bar. So far, the susceptibility of HEA/MEAs to hydrogen assisted cracking (if any) and the especially the underlying hydrogen uptake and diffusion was not within the scientific scope and not investigated in detail yet. For that reason, we focused on the hydrogen absorption the characterization of the hydrogen diffusion and trapping at elevated temperatures in a CoCrFeMnNi-HEA (each element with 20 at.-%) and CoCrNi-MEA, each element with 33.3 at.-%). As reference grade, the commercially available austenitic stainless steel AISI 316L was investigated. High-pressure hydrogen charging was conducted at different pressures in autoclave environment with maximum value of 1,000 bar. Thermal desorption analysis (TDA) via carrier gas hot extraction with coupled mass spectrometry was used with a max. heating rate of 0.5 K/s up to 650 °C. The measured desorption spectra of the different samples were deconvoluted into a defined number of individual peaks. The individually calculated peak temperatures allowed the definition of activation energies for predominant trap sites in the respective materials as well as the percentage share of the totally absorbed hydrogen concentration. The results present for the first time the complex interaction of both MPEAs and high-pressure hydrogen charging. A deconvolution of four peaks was selected and a main desorption peak was identified the dominant hydrogen trap containing the biggest share of the absorbed hydrogen concentration. The chemical composition an austenitic phase of both MPEAs is responsible for delayed hydrogen diffusion and strong, but mostly reversible, trapping. The comparison with the 316L samples showed significantly higher activation energies in the MPEAs, whereas hydrogen was also trapped at very high extraction temperatures. The absorbed maximum hydrogen concentration at 1,000 bar was 130 ppm for the CoCrFeMnNi-HEA, 50 ppm for the CoCrNi-MEA and 80 ppm for the 316L. It is interesting that the CoCrFeMnNi-HEA has obviously a way higher trapping capability compared to the conventional austenitic 316L, which could be a major advantage in terms of resistance to hydrogen assisted cracking.
Covalent organic frameworks (COFs) are a prominent class of organic materials constructed from versatile building blocks via reversible reactions. The quality of imine-linked COFs can be improved by using amine monomers protected with benzophenone forming benzophenone imines. Here, we present a study on substituted benzophenones in COF synthesis via formal transimination. 12 para-substituted N-aryl benzophenone imines, with a range of electron-rich to electron-poor substituents, were prepared and their hydrolysis kinetics were studied spectroscopically. All substituted benzophenone imines can be employed in COF synthesis and lead to COFs with high crystallinity and high porosity. The substituents act innocent to COF formation as the substituted benzophenones are cleaved off. Imines can be tailored to their synthetic demands and utilized in COF formation. This concept can make access to previously unattainable, synthetically complex COF monomers feasible.
In our (dramatically understaffed) X-ray scattering laboratory, developing a systematic, holistic methodology1 let us provide scattering and diffraction information for more than 2100 samples for 200+ projects led by 120+ collaborators over the last five years. Combined with universal, automat-ed data correction pipelines, as well as our analysis and simulation software, this led to more than 40 papers2 in the last 5 years with just over 2 full-time staff members.
While this approach greatly improved the consistency of the results, the consistency of the samples and sample series provided by the users was less reliable nor necessarily reproducible. To address this issue, we built an EPICS-controlled, modular synthesis platform to add to our laboratory. To date, this has prepared over 1200 additional (Metal-Organic Framework) samples for us to meas-ure, analyse and catalogue. By virtue of the automation, the synthesis of these samples is automat-ically documented in excruciating detail, preparing them for upload and exploitation in large-scale materials databases alongside the morphological results obtained from the automated X-ray scat-tering analysis.
Having developed these proof-of-concepts, we find that the consistency of results are greatly im-proved by virtue of their reproducibility, hopefully adding to the reliability of the scientific findings as well. Additionally, the nature of the experiments has changed greatly, with much more emphasis on preparation and careful planning. This talk will discuss the advantages and disadvantages of this highly integrated approach and will touch upon upcoming developments.
Per- and polyfluoroalkyl substances (PFAS) are a large group of more than 10,000 anionic, cationic, zwitterionic or neutral organofluorine surfactants. As a result of continuous and prolific use, mainly in aviation firefighting foams, thousands of industrial and military installations have been found to contain contaminated soil, groundwater and surface water. While liquid chromatography tandem mass spectrometry (LC-MS/MS) is commonly used technique to characterize targeted PFAS in environmental samples, there are more than 10,000 different PFAS known, which have various headgroups and properties. Therefore, several analytical techniques are available to analyse various groups or pools of PFAS or “all” PFAS as a sum parameter. Current decontamination strategies of PFAS-burdened soils mainly consist of adsorption methods using adsorbents for fixation of PFAS in the ground. A second option is the utilization of a “pump and treat” process, cycling polluted soils through a washing plant leading to the concentration of the pollutants in the fine fraction. Both approaches are cost-intensive and not intended for the direct decomposition of all PFAS contaminants. Hence, there is a great demand for innovative developments and chemical treatment technologies, dealing with new strategies of tackling the PFAS problem. Previously, mechanochemical treatment of polychlorinated organic compounds in soils showed an efficient dechlorination. Thus, we investigated mechanochemical treatment of PFAS contaminated soils with various additives in a ball mill and analyzed the PFAS defluorination with gas chromatography mass spectrometry (GC-MS) and liquid chromatography tandem mass spectrometry (LC-MS/MS), respectively, as well es the fluoride mineralization by ion chromatography (IC) and fluorine K-edge X-ray absorption near-edge structure (XANES) spectroscopy.
This contribution provides an overview of the BAMline synchrotron radiation beamline, which specializes in hard X-ray spectroscopy techniques for materials research. The BAMline offers X-ray absorption spectroscopy (XAS), x-ray fluorescence spectroscopy (XRF), and tomography to study materials' electronic structure, chemical composition, and structure. Key capabilities include standard and dispersive XAS for electronic structure, micro-XRF for elemental mapping, coded aperture imaging, and depth-resolved grazing exit XAS. The BAMline enables in situ characterization during materials synthesis and functions for energy, catalysis, corrosion, biology, and cultural heritage applications.
Ongoing developments like the implementation of machine learning techniques for experiment optimization and data analysis will be discussed. For instance, Bayesian optimization is being used to improve beamline alignment and scanning. An outlook to the future, where the BAMline will continue pioneering dynamic and multi-scale characterization, aided by advanced data science methods, to provide unique insights into materials research, will be given.
The structure and composition of ancient gold objects retain information about their long history of manufacture, from the exploitation of the ore to the finishing touches, as well as evidence of their use, deposition, and degradation. By developing an efficient analytical strategy, it is possible to retrieve that information. This chapter sets the necessary foundation 131to explore fully the analytical results presented in the following chapters of this volume. The techniques employed in the analyses of the Egyptian jewellery are described and the analytical parameters provided. For more established techniques, only brief introductions are presented, while more recent developments are presented in greater detail.
Enhancing efficiency at bamline: employing data science and machine learning for x-ray research
(2023)
This talk discusses how data science and machine learning techniques are being applied at the BAM Federal Institute for Materials Research and Testing to enhance efficiency and automation at the BAMLine synchrotron facility. The methods presented include Gaussian processes and Bayesian optimization for beamline adjustment and optimization of X-ray measurements. These statistical techniques allow automated alignment of beamline components and active learning scanning to reduce measurement time.
Additional machine learning methods covered are neural networks for quantification of X-ray fluorescence (XRF) data and decoding coded apertures.
Laser breakdown spectroscopy (LIBS) is a common tool for applications in various fields of science and technology. Originally an atomic analysis technique, LIBS was later extended to molecular analysis due to the transient nature of the laser-induced plasma, which develops from a hot dissociation stage on a nanosecond to several microsecond scale to a relatively cold recombination stage on a scale of 10 to 100 microseconds after breakdown. Molecules formed during the recombination stage or incompletely dissociated after ablation can be efficiently detected, allowing the analysis of "difficult" elements or even molecular isotopes. However, with a small amount of ablated material and a short lifetime of the luminous plasma, analytical signals, especially molecular ones, can be very weak.
Several methods have been proposed for reheating the plasma and increasing its lifetime, for example, a two-pulse LIBS or a LIBS combined with microwave radiation or with an electric spark discharge. Here we propose another one, LIBS combined with a capacitively coupled RF discharge at 13.6 MHz. The advantages of this combination are an increase in the lifetime of atomic and molecular emission and operation in a low-pressure atmosphere, which significantly reduces pressure line broadening and allows high-resolution spectroscopy. Another major advantage is operating in a chemically controlled atmosphere that can predictably drive desired chemical reactions. In this presentation, we will show the first results obtained with RF-LIBS combination. These will include separate and joint characterization of LIBS and RF plasmas and evaluation of its potential for elemental and molecular analysis and for plasma enhanced chemical vapor deposition.
Many applications of LIBS require the measurement of plasma temperature and electron density, which in turn requires knowledge of the integrated line intensity and the shape of the spectral lines. While the integral intensity is preserved as light passes through the spectrometer, the shape emitted by an individual atom or ion is greatly distorted. This is due, firstly, to the transfer of light through the plasma (self-absorption), secondly, to the influence of the instrumental function of the spectrometer, and, thirdly, to the aberrations of the optical system. In addition, processing of spectral information, such as background removal, noise reduction, deconvolution, and line fitting, introduces additional errors in the reconstructed linewidth and line integral, which leads to erroneous temperature and electron density values.
This communication will be devoted to the general shortcomings of spectral data processing and the resulting inaccuracies in determining the plasma parameters. The analysis is based on the use of synthetic spectra generated by plasma with known temperature and particle density. The estimation of errors caused by inadequate processing of the spectral data is made by comparing the initial and determined plasma parameters. As a result, an improved data processing method will be proposed that takes into account the spectrum distortion by the instrumental function and integration on the pixel detector. The former is accounted for by convolution (instead of deconvolution) of the estimated line profile using a predetermined slit function, and the latter is achieved by piecewise integration of the line profile by the pixel detector, taking into account the pixel size and uniform or non-uniform pixel separation. Recommendations will be made for which analytic function best approximates the observed spectral lines and examples will be given for the application of this routine to calibration-free LIBS using both synthetic and experimental data.
In the LIBS literature, almost every second article reports the determination of the plasma temperature using the Boltzmann plot method or the determination of the electron density using the Stark line broadening relation. The first requires the measurement of the integrated intensities of the spectral lines, and the second requires the measurement of the linewidth, under the same assumption of optical thinness. It is taken for granted that this can be easily done either by working with the raw spectra or by fitting an appropriate function to the observed spectral lines. As a rule, reported data are not verified either by an alternative method (e.g., Thomson scattering) or by computer simulations using synthetic spectra.
However, the question of how to extract the necessary information from the raw spectral data is not as simple as it might seem. The quality of such an extraction will depend critically on the type of spectral instrument used, its resolution, and the noise superimposed on the data. The problem is that we do not see the spectrum emitted by the plasma, but the spectrum distorted by the measurement; an exaggerated example of such a distortion is shown in Fig. 1. The elimination of this distortion belongs to the class of inverse problems, the so-called ill-posed problems, whose successful solution crucially depends on the quality of the information available. When it comes to spectroscopy, quality of information primarily means high spectral resolution and low noise. Not all spectrometers used in LIBS can provide the quality needed to solve the inverse problem; this casts doubt on many published plasma measurements.
The current presentation will be devoted to general shortcomings in the processing of spectral data and inaccuracies in the determination of plasma parameters resulting from these shortcomings. The analysis is based on the use of synthetic spectra produced by plasma with known characteristics, i.e., temperature, species densities, and electron density. The estimation of errors caused by inadequate processing of spectral data is made by comparing the initial and reconstructed plasma parameters. Recipes will be given for which the analytic function best approximates the observed spectral lines, and how data processing errors affect accuracy of calibration-free LIBS will be discussed. These issues were only partially covered in previously published works, for example [1, 2, 3].
The aim of the project is to develop an adequate model of laser induced plasma for conditions expected in space missions, i.e., vacuum, or low-pressure CO2 atmosphere. Numerical modeling will help to find optimal experimental parameters for the laser ablation under artificial lunar or Martian environments and obtain both qualitative, in terms of a composition, and quantitative, in terms of an elemental abundance, information about interrogated samples based on spectral data generated by the model. The best operational conditions will be found at a low cost without conducting tedious and time-consuming optimization experiments. The modeling approaches will be supported by machine learning to accelerate the optimization.
The application of multivariate data analysis is essential in extracting the full potential of laser-induced XUV spectroscopy (LIXS) for high-precision elemental mapping. LIXS offers significant advantages over traditional laser-induced breakdown spectroscopy in UV-vis (LIBS), including higher precision and a wider dynamic range,[1,2] while making it possible to determine light elements like lithium and fluorine. However, it is challenged by the presence of unresolved transition arrays (UTAs) for heavier elements. These UTAs add considerable complexity to the spectral data, often concealing crucial information. In this study, we employ well-established multivariate data analysis techniques and intensive data preprocessing to unravel this contained information.
The refined analysis reveals a high level of detail, enabling the precise identification of inhomogeneities within material samples. Our approach has particular relevance for studying aging processes in lithium-ion batteries (LIBs), specifically in relation to varying cathode materials and fluorine-containing polymer binder content. By combining elemental distribution with structural information, this improved method can offer a more comprehensive understanding of sample inhomogeneities and aging processes in LIBs, contributing to the development of more reliable and sustainable battery technologies.
Laser-induced XUV spectroscopy (LIXS) is an emerging technique for elemental mapping. In comparison to conventional laser-induced breakdown spectroscopy in UV-vis (LIBS), it has a higher precision and wider dynamic range, and it is well suited for the quantification light elements like lithium and fluorine. Further it can spot oxidation states. The XUV spectra are produced at a very early stage of the plasma formation. Therefore, effects from plasma evolution on the reproducibility can be neglected. It has been shown, that high-precision elemental quantification in precursor materials for lithium-ion batteries (LIBs) can be performed using LIXS. Based on these results, LIXS mapping was used to investigate aging processes in LIBs. Different cathode materials with varying compositions of fluorine containing polymer binders were compared at different stages of aging. Due to effects comparable to X-ray photoelectron spectroscopy but in reverse, monitoring of changes in the oxidation state is envisioned, which makes information about the chemical environment of the observed elements accessible. The combination of elemental distribution and structural information leads to a better understanding of aging processes in LIBs, and the development of more sustainable and safe batteries.
Improved Data Processing for Accurate Plasma Diagnostics with Implications for Calibration-Free LIBS
(2023)
Many LIBS papers report the determination of plasma temperature using the Boltzmann plot method or the determination of electron density using the Stark line broadening relation. This requires measuring the integrated intensities of the spectral lines and the linewidth under the assumption of optical thinness. It is taken for granted that this can be easily done either by working with the raw spectra or by fitting the appropriate function to the observed spectral lines. However, extracting the necessary information from raw spectral data is not as easy as it might seem. The quality of such extraction will depend to a decisive extent on the type of spectral instrument used. The spectrum emitted by the plasma is distorted by the device; an example is shown in Fig. 1. The elimination of this distortion belongs to the class of inverse problems, the successful solution of which fundamentally depends on the quality of the available information. When it comes to spectroscopy, the quality of information primarily means high spectral resolution and low noise. Not all spectrometers used in LIBS can provide the quality needed to solve the inverse problem; this casts doubt on many published plasma measurements. This communication will be devoted to the general shortcomings of spectral data processing and the inaccuracies in determining the plasma parameters resulting from these shortcomings. The analysis is based on the use of synthetic spectra generated by plasma with known temperature, particle density and electron density. The estimation of errors caused by inadequate processing of spectral data is made by comparing the initial and measured plasma parameters from the spectra. Recommendations will be made for which analytic function best approximates the observed spectral lines, and how data processing errors affect the accuracy of calibration-free LIBS will be discussed. These issues were only partially covered in previously published works, for example [1, 2].
Introduction
Lithium-ion batteries (LIBs) are one key technology to overcome the climate crisis and energy transition challenges. Demands of electric vehicles on higher capacity and power drives research on innovative cathode and anode materials. These high energy-density LIBs are operated at higher voltages, leading to increased electrolyte decay and the current collectors' degradation. Even though this fundamental corrosion process significantly affects battery performance, insufficient research is being done on the aluminum current collector. Fast and convenient analytical methods are needed for monitoring the aging processes in LIBs.
Methods
In this work glow-discharge optical emission spectrometry (GD-OES) was used for depth profile analysis of aged cathode material. The measurements were performed in pulsed radio frequency mode. Under soft and controlled plasma conditions, high-resolution local determination (in depth) of the elemental composition is possible. Scanning electron microscopy (SEM) combined with a focused ion beam (FIB) cutting and energy dispersive X-ray spectroscopy (EDX) was used to confirm GD-OES results and obtain additional information on elemental distribution.
Results
The aging of coin cells manufactured with different cathode materials (LCO, LMO, NMC111, NMC424, NMC532, NMC622, and NMC811) was studied. GD-OES depth profiling of new and aged cathode materials was performed. Quantitative analysis was possible through calibration with synthetic standards and correction by sputter rate. Different amounts of aluminum deposit on the cathode surface were found for different materials. The deposit has its origin in the corrosion of the aluminum current collector. The results are compatible with results from FIB-EDX. However, GD-OES is a faster and less laborious analytical method. Therefore, it will accelerate research on corrosion processes in high energy-density batteries.
Innovative aspects
- Quantitative depth profiling of cathode material
-Monitoring of corrosion processes in high energy-density lithium-ion batteries
- Systematic investigation of the influence of different cathode materials
Per- and polyfluoroalkyl substances (PFAS) are a large group of organofluorine surfactants used in the formulations of thousands of consumer goods. The continuous use of PFAS in household products and the discharge of PFAS from industrial plants into the sewer system have been resulted in contaminated effluents and sewage sludge from wastewater treatment plants (WWTPs) which became an important pathway for PFAS into the environment. Because sewage sludge is often used as fertilizer its application on agricultural soils has been observed as significant input path for PFAS into our food chain. To produce high-quality phosphorus fertilizers for a circular economy from sewage sludge, PFAS and other pollutants (e.g. pesticides and pharmaceuticals) must be separated from sewage sludge. Normally, PFAS are analyzed using PFAS protocols typically with time-consuming extraction steps and LC-MS/MS target quantification. However, for screening of PFAS contaminations in wastewater-based fertilizers also the DGT technique can be used for the PFAS extraction. Afterwards, combustion ion chromatography (CIC) can be applied to analyze the “total” amount of PFAS on the DGT binding layer. The DGT method was less sensitive and only comparable to the extractable organic fluorine (EOF) method values of the fertilizers in samples with >150 µg/kg, because of different diffusion properties for various PFAS, but also kinetic exchange limitations. However, the DGT approach has the advantage that almost no sample preparation is necessary. Moreover, the PFAS adsorption on the DGT binding layer was investigated via surface sensitive spectroscopical methods, such as Fourier-transform infrared (FT-IR) and fluorine K-edge X-ray absorption near-edge structure (XANES) spectroscopy.
DICONDE (Digital Imaging and Communication in Non-Destructive Testing) is an open international standard for storing and exchanging industrial test data and process-related information. The DICONDE standard defines both the semantics for structured storage of data and the network-based communication between two endpoints. This allows many test processes to be mapped digitally and securely, while at the same time meeting normative requirements such as traceability to the tester and test object and reproducibility of test results.
The amount of plant-available phosphorus (P) in soil strongly influences the yield of plants in agriculture. Therefore, various simple chemical extraction methods have been developed to estimate the plant-available P pools in soil. More recently, several experiments with the DGT technique have shown that it has a much better correlation to plant-available P in soils than standard chemical extraction methods (e.g. calcium-acetate-lactate (CAL), Colwell, Olsen, water) when soils with different characteristics are considered. However, the DGT technique cannot give information on the plant-available P species in the soil. Therefore, we combined DGT with solution 31P nuclear magnetic resonance (NMR) spectroscopy. This was achieved by using a modified DGT device in which the diffusive layer had a larger pore size, the binding layer incorporated an adsorption material with a higher capacity, and the device had a larger exposure area. The spectroscopic investigation was undertaken after elution of the deployed DGT binding layer in a NaOH solution. Adsorption tests using solutions of known organic P compounds showed that a sufficient amount of these compounds could be adsorbed on the binding layer in order for them to be analyzed by solution 31P NMR spectroscopy. Furthermore, various intermediates of the hydrolysis of trimetaphosphate in soil could be also analyzed over time.
O3BET Quality Protocols
(2023)
Presentation of the process-oriented approach for the development of the quality protocolls (standard operation procedures and work instructions) for the O3BETs. O3BETs are innovative testing facilities for building envelopes which are developed in the course of the Metabuilding Labs EU Horizon 2020 project.
X-ray refraction is analogous to visible light deflection by matter; it occurs at boundaries between different media. The main difference between visible light and X-rays is that in the latter case deflection angles are very small, from a few seconds to a few minutes of arc (i.e., the refraction index n is near to 1). Importantly, deflection of X-rays is also sensitive to the orientation of the object boundaries. These features make X-ray refraction techniques extremely suitable to a) detect defects such as pores and microcracks and quantify their densities in bulk (not too heavy) materials, and b) evaluate porosity and particle properties such as orientation, size, and spatial distribution (by mapping). While X-ray refraction techniques cannot in general image single defects, they can detect objects with size above a few wavelengths of the radiation.
Such techniques, especially at the Synchrotron BESSY II, Berlin, Germany, can be used in-situ, i.e. when the specimen is subjected to temperatures or external loads.
The use of X-ray refraction analysis yields quantitative information, which can be directly input in kinetics, mechanical and damage models.
We hereby show the application of non-destructive X-ray refraction radiography (SXRR, 2D mapping also called topography) to problems in additive manufacturing:
1) Porosity analysis in PBF-LM-Ti64. Through the use of SXRR, we could not only map the (very sparse) porosity distribution between the layers and quantify it, but also classify, and thereby separate, the filled porosity (unmolten powder) from the keyhole and gas pores (Figure 1).
2) In-situ heat treatment of laser powder bed fusion PBF-LM-AlSi10Mg to monitor microstructure and porosity evolution as a function of temperature (Figure 2). By means of SXRR we indirectly observed the initial eutectic Si network break down into larger particles as a function of increasing temperature. We also could detect the thermally induced porosity (TIP). Such changes in the Si-phase morphology upon heating is currently only possible using scanning electron microscopy, but with a much smaller field-of-view. SXRR also allows observing the growth of some individual pores, usually studied via X-ray computed tomography, but again on much smaller fields-of-view.
Our results show the great potential of in-situ SXRR as a tool to gain in-depth knowledge of the defect distribution and the susceptibility of any material to thermally induced damage and/or microstructure evolution over statistically relevant volumes.
Great complexity characterizes Additive Manufacturing (AM) of metallic components via laser powder bed fusion (PBF-LB/M). Due to this, defects in the printed components (like cracks and pores) are still common. Monitoring methods are commercially used, but the relationship between process data and defect formation is not well understood yet. Furthermore, defects and deformations might develop with a temporal delay to the laser energy input. The component’s actual quality is consequently only determinable after the finished process.
To overcome this drawback, thermographic in-situ testing is introduced. The defocused process laser is utilized for nondestructive testing performed layer by layer throughout the build process. The results of the defect detection via infrared cameras are shown for a research PBF-LB/M machine.
This creates the basis for a shift from in-situ monitoring towards in-situ testing during the AM process. Defects are detected immediately inside the process chamber, and the actual component quality is determined.
Knowledge representation in the materials science and engineering (MSE) domain is a vast and multi-faceted challenge: Overlap, ambiguity, and inconsistency in terminology are common. Invariant and variant knowledge are difficult to align cross-domain. Generic top-level semantic terminology often is too abstract, while MSE domain terminology often is too specific.
The PMDco is designed in direct support of the FAIR principles to address immediate needs of the global experts community and their requirements. The illustrated findings show how the PMDco bridges semantic gaps between high-level, MSE-specific, and other science domain semantics, how the PMDco lowers development and integration thresholds, and how to fuel it from real-world data sources ranging from manually conducted experiments and simulations as well as continuously automated industrial applications.